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2022
Journal
Xu, Y., Yan, X., Sun, B., & Liu, Z. (2022). Global contextual residual convolutional neural networks for motor fault diagnosis under variable-speed conditions. Reliability Engineering & System Safety, 108618.
Ma, Z., Rayhana, R., Feng, K., Liu, Z., Xiao, G., Ruan, Y., & Sangha, J. S. (2022). A Review on Sensing Technologies for High-throughput Plant Phenotyping. IEEE Open Journal of Instrumentation and Measurement.
Zhao, X., Yao, J., Deng, W., Jia, M., & Liu, Z. (2022). Normalized Conditional Variational Auto-Encoder with adaptive Focal loss for imbalanced fault diagnosis of Bearing-Rotor system. Mechanical Systems and Signal Processing, 170, 108826.
Xu, Y., Yan, X., Sun, B., & Liu, Z. (2022). Deep Coupled Visual Perceptual Networks for Motor Fault Diagnosis Under Nonstationary Conditions. IEEE/ASME Transactions on Mechatronics.
Zhang, X., Liu, H., Wang, Z., Dong, H., Ge, J., & Liu, Z. (2022). Anomaly detection of complex magnetic measurements using structured Hankel low-rank modeling and singular value decomposition. Review of Scientific Instruments, 93(4), 045107.
Zhao, X., Yao, J., Deng, W., Ding, P., Zhuang, J., & Liu, Z. (2022). Multi-Scale Deep Graph Convolutional Networks for Intelligent Fault Diagnosis of Rotor-Bearing System Under Fluctuating Working Conditions. IEEE Transactions on Industrial Informatics.
Xu, Y., Yan, X., Sun, B., & Liu, Z. (2022). Hierarchical multiscale dense networks for intelligent fault diagnosis of electromechanical systems. IEEE Transactions on Instrumentation and Measurement, 71, 1-12.
Xu, L., Gao, M., Liu, Z., Li, Q., & Jeon, G. (2022). Accelerated duality-aware correlation filters for visual tracking. Neural Computing and Applications, 1-16.
Wang, T., Bin, J., Renaud, G., Liao, M., Lu, G., & Liu, Z. (2022). Probabilistic method for fatigue crack growth prediction with hybrid prior. International Journal of Fatigue, 106686.
Fu, G., Zou, G., Gao, M., Wang, Z., & Liu, Z. (2022). Image matching based on a structured deep coupled metric learning framework. Signal, Image and Video Processing, 1-9.
Liu, Z., Xiao, G., Liu, H., & Wei, H. (2022). Multi-Sensor Measurement and Data Fusion. IEEE Instrumentation & Measurement Magazine, 25(1), 28-36.
Zhao, X., Yao, J., Deng, W., Ding, P., Ding, Y., Jia, M., & Liu, Z. (2022). Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network. IEEE Transactions on Neural Networks and Learning Systems.
Liu, H., Dong, H., Ge, J., & Liu, Z. (2022). An overview of sensing platform-technological aspects for vector magnetic measurement: A case study of the application in different scenarios. Measurement, 187, 110352.
Lin, J., Fernández, J. A., Rayhana, R., Zaji, A., Zhang, R., Herrera, O. E., ... & Mérida, W. (2022). Predictive analytics for building power demand: day-ahead forecasting and anomaly prediction. Energy and Buildings, 255, 111670.
Conference
Blasch, E., Liu, Z., & Zheng, Y. (2022, May). Advances in deep learning for infrared image processing and exploitation. In Infrared Technology and Applications XLVIII (Vol. 12107, pp. 368-383). SPIE.
Close 2022
2021
Journal
Bin, J., Rahman, C. A., Rogers, S., & Liu, Z. (2021). Tensor-Based Approach for Liquefied Natural Gas Leakage Detection From Surveillance Thermal Cameras: A Feasibility Study in Rural Areas. IEEE Transactions on Industrial Informatics, 17(12), 8122-8130.
Yun, H., Carlone, M., & Liu, Z. (2021). Topic modeling of maintenance logs for linac failure modes and trends identification. Journal of applied clinical medical physics, 23(1), e13477.
Rayhana, R., Jiao, Y., Liu, Z., Wu, A., & Kong, X. (2021). Real-time embedded system for valve detection in water pipelines. Journal of Real-Time Image Processing, 19(2), 247-259.
Xu, Y., Yan, X., Sun, B., Zhai, J., & Liu, Z. (2021). Multireceptive Field Denoising Residual Convolutional Networks for Fault Diagnosis. IEEE Transactions on Industrial Electronics.
Bahrami, Z., Zhang, R., Rayhana, R., & Liu, Z. (2021). An HRCR-CNN Framework for Automated Security Seal Detection on the Shipping Container. IEEE Transactions on Instrumentation and Measurement, 70, 1-13.
Zhang, R., Bahrami, Z., & Liu, Z. (2021). A Vertical Text Spotting Model for Trailer and Container Codes. IEEE Transactions on Instrumentation and Measurement, 70, 1-13.
Yun, H., Rayhana, R., Pant, S., Genest, M., & Liu, Z. (2021). Nonlinear ultrasonic testing and data analytics for damage characterization: A review. Measurement, 186, 110155.
Rayhana, R., Xiao, G., & Liu, Z. (2021). Printed sensor technologies for monitoring applications in smart farming: a review. IEEE Transactions on Instrumentation and Measurement.
Liu, H., Zhao, C., Zhu, J., Ge, J., Dong, H., Liu, Z., & Mrad, N. (2021). Active Detection of Small UXO-Like Targets Through Measuring Electromagnetic Responses With a Magneto-Inductive Sensor Array. IEEE Sensors Journal, 21(20), 23558-23567.
Liu, H., Wang, Z., Zhao, C., Ge, J., Dong, H., & Liu, Z. (2021). Improving the Signal-to-Noise-Ratio of Free Induction Decay Signals Using a New Multilinear Singular Value Decomposition-Based Filter. IEEE Transactions on Instrumentation and Measurement, 70, 1-11.
Liu, H., Wang, X., Zhao, C., Ge, J., Dong, H., & Liu, Z. (2021). Magnetic Dipole Two-Point Tensor Positioning Based on Magnetic Moment Constraints. IEEE Transactions on Instrumentation and Measurement, 70, 1-10.
Liu, H., Wang, X., Zhao, C., Wang, Z., Ge, J., Dong, H., & Liu, Z. (2021). A modular magneto-inductive sensor for low vector magnetic field measurements. Review of Scientific Instruments, 92(8), 085110.
Jian, L., Rayhana, R., Ma, L., Wu, S., Liu, Z., & Jiang, H. (2021). Infrared and Visible Image Fusion Based on Deep Decomposition Network and Saliency Analysis. IEEE Transactions on Multimedia.
Liu, H., Bin, J., Liu, Y., Dong, H., Liu, Z., Mrad, N., & Blasch, E. (2021). SGCast: A New Forecasting Framework for Multilocation Geomagnetic Data With Missing Traces Based on Matrix Factorization. IEEE Transactions on Instrumentation and Measurement, 70, 1-11.
X. Wang, J. Jiang, M. Gao, Z. Liu and C. Zhao, “Activation ensemble generative adversarial network transfer learning for image classification”, Journal of Electronic Imaging, vol.30(1), pp.013016, February 2021.
R. Rayhana, Y. Jiao, Z. Bahrami, Z. Liu, A. Wu and X. Kong, “Valve Detection for Autonomous Water Pipeline Inspection Platform”, IEEE/ASME Transactions on Mechatronics, vol.1(1), pp.1-1, May 2021.
X. Zhao, M. Jia and Z. Liu, “Semi-Supervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System with Limited Labeled Data”, IEEE Transactions on Industrial Informatics, vol.17(8), pp.5450-5460, August 2021.
S. Liu, H. Liu and Z. Liu, “Quantification of pitting corrosion from thermography using deep neural networks”, Review of Scientific Instruments, vol.92(3), pp.035116, March 2021.
H. Liu, S. Liu, Z. Liu, N. Mrad and A. Milani, “Data-driven Approaches for Characterization of Delamination Damage in Composite Materials”, IEEE Transactions on Industrial Electronics, vol.68(3), pp.2532-2542, March 2021.
X. Peng, H. Liu, K. Siggers and Z. Liu, “Pipeline corrosion defect parameterisation with magnetic flux leakage inspection: a contextual representation approach”, Insight - Non-Destructive Testing & Condition Monitoring, vol.63(2), pp.1-8, February 2021.
X. Peng, H. Liu, K. Siggers and Z. Liu, “Automated Box Data Matching for Multi-Modal Magnetic Flux Leakage Inspection of Pipelines”, IEEE Transactions on Magnetics, vol.57(5), pp.1-10, May 2021.
Q. Jin, Z. Liu and S. He, “Investigation on the Mathematical Relation Model of Structural Reliability and Structural Robustness”, Mathematical and Computational Applications, vol.26(2), pp.1-14, March 2021.
Q. Jin and Z. Liu, “Measure point arrangement strategy for in-service continuous girder bridge SHM with consideration of structural robustness (Special Issue of ICAST 2019)”, Journal of Intelligent Material Systems and Structures, pp.1045389X20983886, 2021.
Y. Jiao, R. Rayhana, J. Bin, Z. Liu, A. Wu and X. Kong, “A steerable pyramid autoencoder based framework for anomaly frame detection of water pipeline CCTV inspection”, Measurement, vol.174, pp.109020, April 2021.
R. Rayhana, G. Xiao and Z. Liu, “RFID Sensing Technologies for Smart Agriculture”, IEEE Instrumentation & Measurement Magazine (, vol.24(3), pp.50-60, May 2021.
X. Wang, H. Liu, H. Wang, J. Ge, H. Dong and Z. Liu, “Quantitative analysis of the measurable areas of differential magnetic gradient tensor systems for unexploded ordnance detection”, IEEE Sensors Journal, vol.21(5), pp.5952-5960, March 2021.
Conference
Bin, J., Zhang, R., Du, S., Zheng, C., Liu, X., Blasch, E., & Liu, Z. (2021). Improved Object Detection in Thermal Imaging Through Context Enhancement and Information Fusion: A Case Study in Autonomous Driving,‖.
M. Kang, T. Wang, S. Pant, M. Genest and Z. Liu, “Fault detection and diagnosis for PZT sensors with electro-mechanical impedance technique by using one-dimensional convolutional autoencoder”, Health Monitoring of Structural and Biological Systems XV, vol.11593, pp.1159309, March 2021.
R. Zhang, J. Bin, Z. Liu and E. Blasch, “Image translation to enhance IR2VIS image registration”, Geospatial Informatics XI, vol.11733, pp.117330A, April 2021.
Liu, F., Liu, Z., & Liu, Z. (2021, October). Attentive Contrast Learning Network for Fine-Grained Classification. In Chinese Conference on Pattern Recognition and Computer Vision (PRCV) (pp. 92-104). Springer, Cham.
Close 2021
2020
Journal
H. Song, H. Liu, H. Dong, Z. Liu, J. Ge, Z. Yuan, J. Zhu and X. Luan, “Compressed sensing based tuning algorithm for the sensor of proton precession magnetometers”, Review of Scientific Instruments, vol.91(8), pp.085118, August 2020.
S. Liu, H. Liu, V. John, Z. Liu and E. Blasch, “Enhanced situation awareness through CNN-based deep multimodal image fusion”, Optical Engineering, vol.59(5), pp.053103, May 2020.
H. Liu, X. Wang, H. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Magneto-Inductive Magnetic Gradient Tensor System for Detection of Ferromagnetic Objects”, IEEE Magnetics Letters, vol.11, pp.1-5, February 2020.
R. Zhang, Z. Bahrami, T. Wang and Z. Liu, “An Adaptive Deep Learning Framework for Shipping Container Code Localization and Recognition”, IEEE Transactions on Instrumentation and Measurement, vol.70, pp.1-13, August 2020.
T. Wang, Z. Liu, M. Liao, N. Mrad and G. Lu, “Probabilistic Analysis for Remaining Useful Life Prediction and Reliability Assessment”, IEEE Transactions on Reliability, vol.1(1), pp.1-12, December 2020.
G. Zou, G. Fu, M. Gao, J. Pan and Z. Liu, “A new approach for small sample face recognition with pose variation by fusing Gabor encoding features and deep features”, Multimedia Tools and Applications, vol.79(31), pp.23571-23598, August 2020.
H. Liu, S. Liu, Z. Liu, N. Mrad and A. Milani, “Data-driven Approaches for Characterization of Delamination Damage in Composite Materials”, IEEE Transactions on Industrial Electronics, vol.1(1), pp.1-1, February 2020.
X. Zhao, M. Jia, P. Ding, C. Yang, D. She and Z. Liu, “Intelligent Fault Diagnosis of Multi-Channel Motor-Rotor System based on Multi-manifold Deep Extreme Learning Machine”, IEEE/ASME Transactions on Mechatronics, vol.25(5), pp.2177-2187, October 2020.
U. Anyaoha, A. Zaji and Z. Liu, “Soft computing in estimating the compressive strength for high-performance concrete via concrete composition appraisal”, Construction and Building Materials, vol.257(119472), pp.1-11, October 2020.
G. Wang, Q. Li, L. Wang, Y. Zhang and Z. Liu, “CMFALL: A Cascade and Parallel Multi-state Fall Detection Algorithm Using Waist-mounted Tri-axial Accelerometer Signals”, IEEE Transactions on Consumer Electronics, vol.66(3), pp.261-270, August 2020.
T. Wang, Z. Liu, M. Liao and N. Mrad, “Life prediction for aircraft structure based on Bayesian inference: towards a digital twin ecosystem”, Annual Conference of the PHM Society, vol.12(1), pp.8-8, November 2020.
S. Liu, M. Gao, V. John, Z. Liu and E. Blasch, “Deep Learning Thermal Image Translation for Night Vision Perception”, ACM Transactions on Intelligent Systems and Technology (TIST), vol.12(1), pp.1-18, December 2020.
T. Wang, Z. Liu, G. Lu and J. Liu, “Temporal-spatio graph based spectrum analysis for bearing fault detection and diagnosis”, IEEE Transactions on Industrial Electronics, vol.68(3), pp.2598-2607, March 2020.
H. Liu, X. Wang, H. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Magneto-inductive magnetic gradient tensor system for detection of ferromagnetic objects”, IEEE Magnetics Letters, vol.11, pp.1-5, February 2020.
H. Liu, X. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Magnetic gradient full-tensor fingerprints for metallic objects detection of a security system based on anisotropic magnetoresistance sensor arrays”, AIP Advances, vol.10(015329), pp.1-9, January 2020.
L. Jian, X. Yang, Z. Liu, G. Jeon, M. Gao and D. Chisholm, “SEDRFuse: A Symmetric Encoder-Decoder with Residual Block Network for Infrared and Visible Image Fusion”, IEEE Transactions on Instrumentation and Measurement, vol.70(5002215), pp.1-15, September 2020.
X. Zhao, M. Jia and Z. Liu, “Semi-Supervised Deep Sparse Auto-Encoder with Local and Non-Local Information for Intelligent Fault Diagnosis of Rotating Machinery”, IEEE Transactions on Instrumentation and Measurement, vol.70(3501413), pp.1-12, August 2020.
R. Rayhana, G. Xiao and Z. Liu, “Internet of Things Empowered Smart Greenhouse”, IEEE Journal of Radio Frequency Identification, vol.4(3), pp.195-211, September 2020.
X. Peng, U. Anyaoha, Z. Liu and K. Tsukada, “Analysis of Magnetic Flux Leakage (MFL) Data for Pipeline Corrosion Assessment”, IEEE Transactions on Magnetics, vol.56(6), pp.1-15, June 2020.
R. Rayhana, Y. Jiao, A. Zaji and Z. Liu, “Automated Vision Systems for Condition Assessment of Sewer and Water Pipelines”, IEEE Transactions on Automation Science and Engineering, vol.1(1), pp.1-1, September 2020.
H. Liu, H. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Efficient noise reduction for the free induction decay signal from a proton precession magnetometer with time-frequency peak filtering”, Review of Scientific Instruments, vol.91(4), pp.1-19, April 2020.
C. Zhang, J. Bin, W. Wang, X. Peng, R. Wang, R. Halldearn and Z. Liu, “AIS data driven general vessel destination prediction: A random forest based approach”, Transportation Research Part C: Emerging Technologies, vol.118, pp.1-19, September 2020.
F. Shi, X. Peng, Z. Liu, E. Li and Y. Hu, “A data-driven approach for pipe deformation prediction based on soil properties and weather conditions”, Sustainable Cities and Society, vol.55(102012), pp.1-11, April 2020.
X. Zhao, M. Jia, J. Bin, T. Wang and Z. Liu, “Multiple-Order Graphical Deep Extreme Learning Machine for Unsupervised Fault Diagnosis of Rolling Bearing”, IEEE Transactions on Instrumentation and Measurement, vol.70, pp.1-12, December 2020.
A. Sholehkerdar, J. Tavakoli and Z. Liu, “Theoretical analysis of Tsallis entropy-based quality measure for weighted averaging image fusion”, Information Fusion, vol.58, pp.69-81, June 2020.
M. Khateri, F. Shabanzade, F. Mirzapour, A. Zaji and Z. Liu, “A Variational Approach for Fusion of Panchromatic and Multi-Spectral Images Using a New Spatial-Spectral Consistency Term”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.13, pp.3421-3436, June 2020.
T. Wang, Z. Liu and N. Mrad, “A probabilistic framework for remaining useful life prediction of bearings”, IEEE Transactions on Instrumentation and Measurement, vol.70(3503412), pp.1-12, October 2020.
H. Geirnhas, Z. Liu, X. Chen, W. Li, C. Sensors, G. Brasseur, N. Paulter, W. Recorder, B. Boyer, S. Tilden, T. Linnenbrink, P. Techniques, J. Subcommittee, S. Rapuano, O. A, O. Postolache, J. Scharcanski, G. Giakos, M. Zervakis, M. Siegel, F. Scotti, A. Lay-Ekuakille and G. Xiao, “2020 IEEE IMS Technical Committees”, IEEE Instrumentation & Measurement Magazine, September 2020.
J. Bin, B. Gardiner, E. Li and Z. Liu, “Multi-Source Urban Data Fusion for Property Value Assessment: A Case Study in Philadelphia”, Neurocomputing, vol.404(Sep), pp.70-83, May 2020.
X. Zhao, M. Jia, P. Ding, C. Yang, D. She, L. Zhu and Z. Liu, “A New Intelligent Weak Fault Recognition Framework for Rotating Machinery”, International Journal of Acoustics and Vibration, vol.25(3), pp.461-479, September 2020.
Conference
Z. Bahrami, R. Zhang, R. Rayhana, T. Wang and Z. Liu, “Optimized Deep Neural Network Architectures with Anchor Box optimization for Shipping Container Corrosion Inspection”, 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pp.1328-1333, December 2020.
T. Wang, Z. Liu, X. Zhao, M. Liao and N. Mrad, “Bayesian-Based Method for the Remaining Useful Life and Reliability Prediction of Steel Structure”, 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), pp.1-6, August 2020.
E. P, Y. Zheng, S. Liu and Z. Liu, “Multi-modal Video Fusion for Context-aided Tracking”, 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp.1-8, July 2020.
J. Bin, M. Kang and Z. Liu, “GPU-Accelerated Tensor Decomposition for Moving Object Detection from Multimodal Imaging”, 2020 IEEE Sensors, pp.1-4, October 2020.
L. Xu, Q. Li, J. Jiang, G. Zou, Z. Liu and M. Gao, “Adaptive Spatio-Temporal Regularized Correlation Filters for UAV-based Tracking”, Proceedings of the Asian Conference on Computer Vision, 2020.
Q. Jin and Z. Liu, “Structural Robustness-based SHM Point Arrangement Strategy for In-service Cable-stayed Bridge Subjected to Cable Damage Effect”, 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), pp.1-6, August 2020.
X. Zhao, Z. Liu, T. Wang, J. Bin and M. Jia, “Unsupervised Fault Diagnosis of Machine via Multiple-Order Graphical Deep Extreme Learning Machine”, 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), pp.1-6, August 2020.
R. Rayhana, Y. Jiao, Z. Liu, A. Wu and X. Kong, “Water pipe valve detection by using deep neural networks”, Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems, vol.11382, pp.1138205-1-8, April 2020.
E. Blasch, Z. Liu and Y. Zheng, “Image fusion for context-aided automatic target recognition”, Automatic Target Recognition XXX, vol.11394, pp.113940U-1-12, May 2020.
Close 2020
2019
Journal
G. Bhatnagar, Z. Liu and Q. Jonathan, “Multimodal medical image fusion in NSCT domain”, Big Data in Multimodal Medical Imaging, pp.23, November 2019.
F. Ruffa, C. De, R. Morello and Z. Liu, “Temperature Sensing and Evaluation of Thermal Effects on Battery Packs for Automotive Applications”, IEEE Sensors Journal, vol.19(23), pp.11634-11645, December 2019.
J. Bin, B. Gardiner, Z. Liu and E. Li, “Attention-based multi-modal fusion for improved real estate appraisal: a case study in Los Angeles”, Multimedia Tools and Applications, vol.79(Nov), pp.31163–31184, July 2019.
Q. Jin and Z. Liu, “In-service Bridge SHM Monitoring Point Arrangement with Consideration of Structural Robustness”, Journal of Civil Structural Health Monitoring, vol.9(4), pp.543-554, September 2019.
A. Sholehkerdar, J. Tavakoli and Z. Liu, “In-depth analysis of Tsallis entropy based measures for image fusion quality assessment”, Optical Engineering, vol.58(3), pp.033102-1-16, 2019.
Q. Jin, Z. Liu, J. Bin and W. Ren, “Predictive Analytics of In-Service Bridge Structural Performance from SHM Data Mining Perspective: A Case Study”, Shock and Vibration, vol.2019, pp.1-11, July 2019.
H. Yun, C. Zhang, C. Hou and Z. Liu, “An Adaptive Approach for Ice Detection in Wind Turbine with Inductive Transfer Learning”, IEEE Access, vol.7, pp.122205-122213, July 2019.
J. Xiang, J. Bin and Z. Liu, “Software as a service: the future of NDI data analysis in the cloud”, Insight - Non-Destructive Testing and Condition Monitoring, vol.61(6), pp.341-346, June 2019.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “A fusion of principal component analysis and singular value decomposition based multivariate denoising algorithm for free induction decay transversal data”, Review of Scientific Instruments, vol.90(3), pp.035116, March 2019.
H. Liu, Z. Liu, H. Dong, J. Ge, Z. Yuan, J. Zhu, H. Zhang and X. Zeng, “Recurrent Neural Network-Based Approach for Sparse Geomagnetic Data Interpolation and Reconstruction”, IEEE Access, vol.7, pp.33173-33179, March 2019.
F. Wang, W. Lin, Z. Liu and X. Qiu, “Pressure Signal Enhancement of Slowly Increasing Leaks Using Digital Compensator Based on Acoustic Sensor”, Sensors, vol.19(19), pp.4317, January 2019.
X. Zhao, M. Jia, Z. Liu, P. Ding, C. Yang and L. Zhu, “Fault Diagnosis Framework of Rolling Bearing using Adaptive Sparse Contrative Auto-encoder with Optimized Unsupervised Extreme Learning Machine”, IEEE Access, vol.8, pp.99154-99170, December 2019.
T. Wang, Z. Liu and G. Lu, “Bearing Condition Monitoring based on the Indicator Generated in Time-frequency Domain”, Annual Conference of the PHM Society, vol.11(1), September 2019.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “High-precision sensor tuning of proton precession magnetometer by combining principal component analysis and singular value decomposition”, IEEE Sensors Journal, vol.19(21), pp.9688-9696, July 2019.
H. Liu, Z. Liu, B. Taylor and D. Haobin, “Matching pipeline In-line inspection data for corrosion characterization”, NDT & E International, vol.101, pp.44-52, January 2019.
J. Bin, B. Gardiner, E. Li and Z. Liu, “Peer-Dependence Valuation Model for Real Estate Appraisal”, Data-Enabled Discovery and Applications, vol.3(2), pp.1-11, January 2019.
M. Gao, J. Jiang, G. Zou, V. John and Z. Liu, “RGB-D-Based Object Recognition Using Multimodal Convolutional Neural Networks: A Survey”, IEEE Access, vol.7(1), pp.43110-43136, 2019.
Q. Li, L. Lu, Z. Li, W. Wu, Z. Liu, G. Jeon and X. Yang, “Coupled GAN with Relativistic Discriminators for Infrared and Visible Images Fusion”, IEEE Sensors Journal, vol.0(0), pp.1-22, June 2019.
H. Liu, W. Luo, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Design and implementation of a tuning-matching framework for a high-sensitivity broad band proton precession magnetometer sensing coil”, IEEE Sensors Journal, vol.20(1), pp.127-134, September 2019.
V. John, Z. Liu, S. Mita and Y. Xu, “Stereo vision-based vehicle localization in point cloud maps using multiswarm particle swarm optimization”, Signal, Image and Video Processing, vol.13, pp.805-812, January 2019.
H. Liu, W. Luo, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Design and Implementation of a Tuning-Matching Framework for a High-Sensitivity Broad Band Proton Precession Magnetometer Sensing Coil”, IEEE Sensors Journal, vol.20(1), pp.127-134, September 2019.
G. Wang, Q. Li, L. Wang, Y. Zhang and Z. Liu, “Elderly fall detection with an accelerometer using lightweight neural networks”, Electronics, vol.8(11), pp.1354, November 2019.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Efficient Performance Optimization for the Magnetic Data Readout From a Proton Precession Magnetometer With Low-Rank Constraint”, IEEE Transactions on Magnetics, vol.55(8), pp.1-4, August 2019.
H. Liu, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Adaptive pre-whiten filtering for the free induction decay transversal signal in weak magnetic detection”, Review of Scientific Instruments, vol.90, pp.104502, October 2019.
F. Wang, W. Lin, Z. Liu and X. Qiu, “Pipeline Leak Detection and Location Based on Model-Free Isolation of Abnormal Acoustic Signals”, Energies, vol.12(16), pp.3172-1-18, August 2019.
F. Shabanzade, M. Khateri and Z. Liu, “MR and PET Image Fusion Using Nonparametric Bayesian Joint Dictionary Learning”, IEEE Sensors Letters, vol.3(7), pp.1-4, July 2019.
L. Lu, G. Zhu, X. Yang, K. Zhou, Z. Liu and W. Wu, “Affine Projection Algorithm based High-Order Error Power for Partial Discharge Denoising in Power Cables”, IEEE Transactions on Instrumentation and Measurement, vol.69(4), pp.1821-1832, May 2019.
Conference
Z. Li, J. Yang, Z. Liu, X. Yang, G. Jeon and W. Wu, “Feedback network for image super-resolution”, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.3867-3876, 2019.
X. Peng, K. Siggers and Z. Liu, “Multi-MFL Measurement Assessment using Gaussian Mixture Model”, 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC), pp.529-534, August 2019.
S. Liu, X. Peng and Z. Liu, “Image Quality Assessment through Contour Detection”, 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), pp.1413-1417, June 2019.
G. Wang, Z. Liu and Q. Li, “Fall Detection with Neural Networks”, 2019 IEEE International Flexible Electronics Technology Conference (IFETC), pp.1-7, August 2019.
X. Peng, C. Zhang, U. Anyaoha, K. Siggers and Z. Liu, “Parameterizing magnetic flux leakage data for pipeline corrosion defect retrieval”, 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), pp.2665-2670, June 2019.
U. Anyaoha, X. Peng and Z. Liu, “Concrete performance prediction using boosting smooth transition regression trees (BooST)”, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII, vol.10971, pp.109710I, April 2019.
M. Gao, J. Jiang, L. Ma, S. Zhou, G. Zou, J. Pan and Z. Liu, “Violent crowd behavior detection using deep learning and compressive sensing”, 2019 Chinese Control And Decision Conference (CCDC), pp.5329-5333, June 2019.
E. Blasch, Z. Liu, Y. Zheng, U. Majumder, A. Aved and P. Zulch, “Multisource deep learning for situation awareness”, SPIE Defense + Commercial Sensing, vol.10988, May 2019.
X. Fu, C. Zhang, X. Peng, L. Jian and Z. Liu, “Towards end-to-end pulsed eddy current classification and regression with CNN”, 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp.1-5, May 2019.
G. Zou, G. Fu, X. Peng, Z. Liu and M. Gao, “Multi-supervised CML for Small Sample Low-resolution Image Matching”, 2019 Chinese Automation Congress (CAC), pp.1046-1051, November 2019.
J. Lin, K. Ranslam, F. Shi, M. Figurski and Z. Liu, “Data Migration from Operating EMRs to OpenEMR with Mirth Connect.”, ITCH, pp.288-292, January 2019.
Close 2019
2018
Journal
F. Shi, Y. Liu, Z. Liu and E. Li, “Prediction of pipe performance with stacking ensemble learning based approaches”, Journal of Intelligent & Fuzzy Systems(Preprint), pp.1-11, 2018.
V. John, Z. Liu, S. Mita, C. Guo and K. Kidono, “Real-time road surface and semantic lane estimation using deep features”, Signal, Image and Video Processing, vol.12(6), pp.1133-1140, September 2018.
H. Liu, Z. Liu, S. Liu, Y. Liu, J. Bin, F. Shi and H. Dong, “A nonlinear regression application via machine learning techniques for geomagnetic data reconstruction processing”, IEEE Transactions on Geoscience and Remote Sensing, vol.57(1), pp.128-140, July 2018.
Z. Liu, E. Blasch, G. Bhatnagar, V. John, W. Wu and R. S, “Fusing Synergistic Information from Multi-Sensor Images: An Overview from Implementation to Performance Assessment”, Information Fusion, vol.42, pp.127-145, 2018.
H. Liu, H. Dong, Z. Liu, J. Ge, W. Luo, C. Zhang, Z. Yuan, J. Zhu and H. Zhang, “A comprehensive study on the weak magnetic sensor character of different geometries for proton precession magnetometer”, Journal of Instrumentation, vol.13(09), pp.1-18, September 2018.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Apparatus and method for efficient sampling of critical parameters demonstrated by monitoring an overhauser geomagnetic sensor”, AIP Review of Scientific Instruments, vol.89(12), pp.125109–1–8, November 2018.
Y. Liu, S. Liu, H. Liu, C. Mandache and Z. Liu, “Pulsed Eddy Current Data Analysis for the Characterization of the Second-Layer Discontinuities”, Journal of Nondestructive Evaluation, vol.38(7), pp.8, November 2018.
H. Liu, H. Dong, Z. Liu and G. Jian, “Application of Hilbert-Huang Decomposition to Reduce Noise and Characterize for NMR FID Signal of Proton Precession Magnetometer”, Instruments and Experimental Techniques, vol.61(1), pp.55-64, January 2018.
Z. Liu, N. Meyendorf and N. Mrad, “The role of data fusion in predictive maintenance using digital twin”, AIP Conference Proceedings, vol.1949(1), pp.020023, April 2018.
V. John, A. Boyali, H. Tehrani, K. Ishimaru, M. Konishi, Z. Liu and S. Mita, “Estimation of Steering Angle and Collision Avoidance for Automated Driving using Deep Mixture of Experts”, IEEE Transactions on Intelligent Vehicles, vol.3(4), pp.571-584, December 2018.
Y. Huang, W. Li, M. Gao and Z. Liu, “Algebraic multi-grid based multi-focus image fusion using watershed algorithm”, IEEE Access, vol.6(1), pp.47082-47091, 2018.
Book
Y. Zheng, E. Blasch and Z. Liu, “Multispectral Image Fusion and Colorization”, pp.396, April 2018.
Y. Zheng, E. Blasch and Z. Liu, “Multispectral image fusion and colorization”, vol.481, March 2018.
Z. Liu, N. Meyendorf and N. Mrad, “The role of data fusion in predictive maintenance using digital twin”, vol.1949(1), pp.020023, April 2018.
Conference
C. Zhang, J. Bin and Z. Liu, “Wind turbine ice assessment through inductive transfer learning”, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp.1-6, May 2018.
F. Shi, X. Peng, H. Liu, Y. Hu, Z. Liu and E. Li, “Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods”, Smart Structures and NDE for Industry 4.0, vol.10602, pp.1060207, March 2018.
S. Liu, V. John, E. Blasch, Z. Liu and Y. Huang, “IR2VI: enhanced night environmental perception by unsupervised thermal image translation”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.1153-1160, 2018.
H. Liu, Y. Liu, S. Liu, Z. Liu, J. Ge, H. Song, Z. Yuan, J. Zhu, H. Zhang and H. Dong, “What can machine learning do for geomagnetic data processing? A reconstruction application”, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp.1-6, May 2018.
Q. Jin, J. Bin, W. Ren and Z. Liu, “Structural Performance Analysis and Prediction for In-Service Bridge with SHM Data Mining”, Canadian Society for Civil Engineering (CSCE) 2018 Annual Conference, pp.GC177-1-11, June 2018.
E. Blasch, S. Liu, Z. Liu and Y. Zheng, “Deep Learning Measures of Effectiveness”, NAECON 2018-IEEE National Aerospace and Electronics Conference, pp.254-261, July 2018.
S. Liu, V. John, E. Blasch, Z. Liu and Y. Huang, “IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.1153-1160, 2018.
Close 2018
2017
Journal
F. Wang, W. Lin, Z. Liu, S. Wu and X. Qiu, “Pipeline Leak Detection by Using Time-Domain Statistical Features”, IEEE Sensors Journal, vol.17(19), pp.6431-6442, August 2017.
G. Bhatnagar and Z. Liu, “Multi-sensor fusion based on local activity measure”, IEEE Sensors Journal, vol.17(22), pp.7487-7496, October 2017.
R. Morello, S. Mukhopadhyay, E. Gaura, Z. Liu, D. Slomovitz, S. Ranjan and U. Onyewuchi, “Guest editorial special issue on smart sensors for smart grids and smart cities”, IEEE Sensors Journal, vol.17(23), pp.7594-7595, November 2017.
V. John, Q. Long, Y. Xu, Z. Liu and S. Mita, “Sensor Fusion and Registration of Lidar and Stereo Camera without Calibration Objects”, IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences, vol.100(2), pp.499-509, February 2017.
Z. Liu, E. Blasch and J. Vijay, “Statistical comparison of image fusion algorithms: Recommendations”, Information Fusion, vol.36, pp.251-260, July 2017.
H. Liu, H. Dong, Z. Liu, J. Ge, B. Bai and C. Zhang, “Noise characterization for the FID signal from proton precession magnetometer”, Journal of Instrumentation, vol.12, pp.1-14, July 2017.
H. Liu, H. Dong, Z. Liu, J. Ge, B. Bai and C. Zhang, “Construction of an Overhauser magnetic gradiometer and the applications in geomagnetic observation and ferromagnetic target localization”, Journal of Instrumentation, vol.12(10), pp.T10008, October 2017.
V. John, S. Tsuchizawa, Z. Liu and S. Mita, “Fusion of thermal and visible cameras for the application of pedestrian detection”, Signal, Image and Video Processing, vol.11(3), pp.517-524, March 2017.
L. Zhao, R. Ichise, Z. Liu, S. Mita and Y. Sasaki, “Ontology-based driving decision making: A feasibility study at uncontrolled intersections”, IEICE TRANSACTIONS on Information and Systems, vol.100(7), pp.1425-1439, July 2017.
Conference
H. Liu, S. Liu, Z. Liu, N. Mrad and H. Dong, “Prognostics of damage growth in composite materials using machine learning techniques”, 2017 IEEE International Conference on Industrial Technology (ICIT), pp.1042-1047, March 2017.
V. John, Y. Xu, S. Mita, Q. Long and Z. Liu, “Registration of GPS and stereo vision for point cloud localization in intelligent vehicles using particle swarm optimization”, International Conference on Swarm Intelligence, pp.209-217, July 2017.
J. Bin, S. Tang, Y. Liu, G. Wang, B. Gardiner, Z. Liu and E. Li, “Regression model for appraisal of real estate using recurrent neural network and boosting tree”, 2017 2nd IEEE international conference on computational intelligence and applications (ICCIA), pp.209-213, September 2017.
F. Shi, Z. Liu and E. Li, “Prediction of pipe performance with ensemble machine learning based approaches”, 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC), pp.408-414, August 2017.
Z. Liu and H. Liu, “Experimenting capacitive sensing technique for structural integrity assessment”, 2017 IEEE International Conference on Industrial Technology (ICIT), pp.922-927, March 2017.
Book Chapter
R. Qi, C. Feng, Z. Liu and N. Mrad, “Blockchain-powered internet of things, e-governance and e-democracy”, pp.509-520, 2017.
R. Morello, S. C, Z. Liu, D. Slomovitz and S. Ranjan, “Advances on sensing technologies for smart cities and power grids: A review”, vol.17(23), pp.7596-7610, August 2017.
Book
S. Liu, V. John and Z. Liu, “On the Prospects of Using Deep Learning for Surveillance and Security Applications”, vol.31, pp.218, 2017.
Close 2017
2016
Conference
Z. Liu, G. Monte and V. Huang, “ISO/IEC/IEEE P21451-001 standard for signal treatment of sensory data”, 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), pp.766-771, June 2016.
L. Zhao, R. Ichise, Y. Sasaki, Z. Liu and T. Yoshikawa, “Fast decision making using ontology-based knowledge base”, 2016 IEEE Intelligent Vehicles Symposium (Gothenburg, Sweden, June 19-22, 2016), pp.173-178, 2016.
Journal
Y. Song, W. Wu, Z. Liu, X. Yang, K. Liu and W. Lu, “An Adaptive Pansharpening Method by Using Weighted Least Squares Filter”, IEEE Geoscience and Remote Sensing Letters, vol.13(1), pp.18-22, January 2016.
B. Qia, V. John, Z. Liu and S. Mita, “Pedestrian detection from thermal images: A sparse representation based approach”, Infrared Physics & Technology, vol.76, pp.157-167, May 2016.
Close 2016
2015
Conference
V. John, S. Mita, Z. Liu and B. Qi, “Pedestrian detection in thermal images using adaptive fuzzy C-means clustering and convolutional neural networks”, 2015 14th IAPR international conference on machine vision applications (MVA), pp.246-249, May 2015.
V. John, Q. Long, Z. Liu and S. Mita, “Automatic Calibration and Registration of Lidar and Stereo Camera without Calibration Objects”, IEEE International Conference on Vehicular Electronics and Safety, 2015.
Z. Liu, R. Morello and W. Wu, “Experiments on battery capacity estimation”, 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, pp.863-868, May 2015.
V. John, Z. Liu, C. Guo, S. Mita and K. Kidono, “Real-time lane estimation using deep features and extra trees regression”, Image and Video Technology, pp.721-733, November 2015.
Journal
G. Bhatnagar and Z. Liu, “A novel image fusion framework for night-vision navigation and surveillance”, Signal, Image and Video Processing, vol.9(1), pp.165-175, December 2015.
V. John, K. Yoneda, Z. Liu and S. Mita, “Saliency Map Generation by the Convolutional Neural Network for Real-Time Traffic Light Detection Using Template Matching”, Computational Imaging, IEEE Transactions on, vol.1(3), September 2015.
G. Bhatnagar, Q. Jonathan and Z. Liu, “A new contrast based multimodal medical image fusion framework”, Neurocomputing, vol.157, pp.143-152, June 2015.
W. Wu, Z. Liu and Y. He, “Classification of defects with ensemble methods in the automated visual inspection of sewer pipes”, Pattern Analysis and Applications, vol.18(2), pp.263-276, May 2015.
Book Chapter
Z. Liu, H. Ukida, K. Niel and P. Ramuhalli, “Industrial inspection with open eyes: Advance with machine vision technology”, pp.1-37, 2015.
Book
Z. Liu, H. Ukida, P. Ramuhalli and K. Niel, “Integrated Imaging and Vision Techniques for Industrial Inspection”, pp.1-541, 2015.
Close 2015
2021
Journal
X. Wang, J. Jiang, M. Gao, Z. Liu and C. Zhao, “Activation ensemble generative adversarial network transfer learning for image classification”, Journal of Electronic Imaging, vol.30(1), pp.013016, February 2021.
R. Rayhana, Y. Jiao, Z. Bahrami, Z. Liu, A. Wu and X. Kong, “Valve Detection for Autonomous Water Pipeline Inspection Platform”, IEEE/ASME Transactions on Mechatronics, vol.1(1), pp.1-1, May 2021.
X. Zhao, M. Jia and Z. Liu, “Semi-Supervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System with Limited Labeled Data”, IEEE Transactions on Industrial Informatics, vol.17(8), pp.5450-5460, August 2021.
S. Liu, H. Liu and Z. Liu, “Quantification of pitting corrosion from thermography using deep neural networks”, Review of Scientific Instruments, vol.92(3), pp.035116, March 2021.
H. Liu, S. Liu, Z. Liu, N. Mrad and A. Milani, “Data-driven Approaches for Characterization of Delamination Damage in Composite Materials”, IEEE Transactions on Industrial Electronics, vol.68(3), pp.2532-2542, March 2021.
X. Peng, H. Liu, K. Siggers and Z. Liu, “Pipeline corrosion defect parameterisation with magnetic flux leakage inspection: a contextual representation approach”, Insight - Non-Destructive Testing & Condition Monitoring, vol.63(2), pp.1-8, February 2021.
X. Peng, H. Liu, K. Siggers and Z. Liu, “Automated Box Data Matching for Multi-Modal Magnetic Flux Leakage Inspection of Pipelines”, IEEE Transactions on Magnetics, vol.57(5), pp.1-10, May 2021.
J. Bin, C. Ashiq, S. Rogers and Z. Liu, “Tensor-based Approach for Liquefied Natural Gas Leakage Detection from Surveillance Thermal Cameras: A Feasibility Study in Rural Areas”, IEEE Transactions on Industrial Informatics, vol.1(1), pp.1-1, March 2021.
Q. Jin, Z. Liu and S. He, “Investigation on the Mathematical Relation Model of Structural Reliability and Structural Robustness”, Mathematical and Computational Applications, vol.26(2), pp.1-14, March 2021.
Q. Jin and Z. Liu, “Measure point arrangement strategy for in-service continuous girder bridge SHM with consideration of structural robustness (Special Issue of ICAST 2019)”, Journal of Intelligent Material Systems and Structures, pp.1045389X20983886, 2021.
Y. Jiao, R. Rayhana, J. Bin, Z. Liu, A. Wu and X. Kong, “A steerable pyramid autoencoder based framework for anomaly frame detection of water pipeline CCTV inspection”, Measurement, vol.174, pp.109020, April 2021.
R. Rayhana, G. Xiao and Z. Liu, “RFID Sensing Technologies for Smart Agriculture”, IEEE Instrumentation & Measurement Magazine (, vol.24(3), pp.50-60, May 2021.
X. Wang, H. Liu, H. Wang, J. Ge, H. Dong and Z. Liu, “Quantitative analysis of the measurable areas of differential magnetic gradient tensor systems for unexploded ordnance detection”, IEEE Sensors Journal, vol.21(5), pp.5952-5960, March 2021.
Conference
M. Kang, T. Wang, S. Pant, M. Genest and Z. Liu, “Fault detection and diagnosis for PZT sensors with electro-mechanical impedance technique by using one-dimensional convolutional autoencoder”, Health Monitoring of Structural and Biological Systems XV, vol.11593, pp.1159309, March 2021.
R. Zhang, J. Bin, Z. Liu and E. Blasch, “Image translation to enhance IR2VIS image registration”, Geospatial Informatics XI, vol.11733, pp.117330A, April 2021.
Close 2021
2020
Journal
H. Song, H. Liu, H. Dong, Z. Liu, J. Ge, Z. Yuan, J. Zhu and X. Luan, “Compressed sensing based tuning algorithm for the sensor of proton precession magnetometers”, Review of Scientific Instruments, vol.91(8), pp.085118, August 2020.
S. Liu, H. Liu, V. John, Z. Liu and E. Blasch, “Enhanced situation awareness through CNN-based deep multimodal image fusion”, Optical Engineering, vol.59(5), pp.053103, May 2020.
H. Liu, X. Wang, H. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Magneto-Inductive Magnetic Gradient Tensor System for Detection of Ferromagnetic Objects”, IEEE Magnetics Letters, vol.11, pp.1-5, February 2020.
R. Zhang, Z. Bahrami, T. Wang and Z. Liu, “An Adaptive Deep Learning Framework for Shipping Container Code Localization and Recognition”, IEEE Transactions on Instrumentation and Measurement, vol.70, pp.1-13, August 2020.
T. Wang, Z. Liu, M. Liao, N. Mrad and G. Lu, “Probabilistic Analysis for Remaining Useful Life Prediction and Reliability Assessment”, IEEE Transactions on Reliability, vol.1(1), pp.1-12, December 2020.
G. Zou, G. Fu, M. Gao, J. Pan and Z. Liu, “A new approach for small sample face recognition with pose variation by fusing Gabor encoding features and deep features”, Multimedia Tools and Applications, vol.79(31), pp.23571-23598, August 2020.
H. Liu, S. Liu, Z. Liu, N. Mrad and A. Milani, “Data-driven Approaches for Characterization of Delamination Damage in Composite Materials”, IEEE Transactions on Industrial Electronics, vol.1(1), pp.1-1, February 2020.
X. Zhao, M. Jia, P. Ding, C. Yang, D. She and Z. Liu, “Intelligent Fault Diagnosis of Multi-Channel Motor-Rotor System based on Multi-manifold Deep Extreme Learning Machine”, IEEE/ASME Transactions on Mechatronics, vol.25(5), pp.2177-2187, October 2020.
U. Anyaoha, A. Zaji and Z. Liu, “Soft computing in estimating the compressive strength for high-performance concrete via concrete composition appraisal”, Construction and Building Materials, vol.257(119472), pp.1-11, October 2020.
G. Wang, Q. Li, L. Wang, Y. Zhang and Z. Liu, “CMFALL: A Cascade and Parallel Multi-state Fall Detection Algorithm Using Waist-mounted Tri-axial Accelerometer Signals”, IEEE Transactions on Consumer Electronics, vol.66(3), pp.261-270, August 2020.
T. Wang, Z. Liu, M. Liao and N. Mrad, “Life prediction for aircraft structure based on Bayesian inference: towards a digital twin ecosystem”, Annual Conference of the PHM Society, vol.12(1), pp.8-8, November 2020.
S. Liu, M. Gao, V. John, Z. Liu and E. Blasch, “Deep Learning Thermal Image Translation for Night Vision Perception”, ACM Transactions on Intelligent Systems and Technology (TIST), vol.12(1), pp.1-18, December 2020.
T. Wang, Z. Liu, G. Lu and J. Liu, “Temporal-spatio graph based spectrum analysis for bearing fault detection and diagnosis”, IEEE Transactions on Industrial Electronics, vol.68(3), pp.2598-2607, March 2020.
H. Liu, X. Wang, H. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Magneto-inductive magnetic gradient tensor system for detection of ferromagnetic objects”, IEEE Magnetics Letters, vol.11, pp.1-5, February 2020.
H. Liu, X. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Magnetic gradient full-tensor fingerprints for metallic objects detection of a security system based on anisotropic magnetoresistance sensor arrays”, AIP Advances, vol.10(015329), pp.1-9, January 2020.
L. Jian, X. Yang, Z. Liu, G. Jeon, M. Gao and D. Chisholm, “SEDRFuse: A Symmetric Encoder-Decoder with Residual Block Network for Infrared and Visible Image Fusion”, IEEE Transactions on Instrumentation and Measurement, vol.70(5002215), pp.1-15, September 2020.
X. Zhao, M. Jia and Z. Liu, “Semi-Supervised Deep Sparse Auto-Encoder with Local and Non-Local Information for Intelligent Fault Diagnosis of Rotating Machinery”, IEEE Transactions on Instrumentation and Measurement, vol.70(3501413), pp.1-12, August 2020.
R. Rayhana, G. Xiao and Z. Liu, “Internet of Things Empowered Smart Greenhouse”, IEEE Journal of Radio Frequency Identification, vol.4(3), pp.195-211, September 2020.
X. Peng, U. Anyaoha, Z. Liu and K. Tsukada, “Analysis of Magnetic Flux Leakage (MFL) Data for Pipeline Corrosion Assessment”, IEEE Transactions on Magnetics, vol.56(6), pp.1-15, June 2020.
R. Rayhana, Y. Jiao, A. Zaji and Z. Liu, “Automated Vision Systems for Condition Assessment of Sewer and Water Pipelines”, IEEE Transactions on Automation Science and Engineering, vol.1(1), pp.1-1, September 2020.
H. Liu, H. Wang, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and X. Luan, “Efficient noise reduction for the free induction decay signal from a proton precession magnetometer with time-frequency peak filtering”, Review of Scientific Instruments, vol.91(4), pp.1-19, April 2020.
C. Zhang, J. Bin, W. Wang, X. Peng, R. Wang, R. Halldearn and Z. Liu, “AIS data driven general vessel destination prediction: A random forest based approach”, Transportation Research Part C: Emerging Technologies, vol.118, pp.1-19, September 2020.
F. Shi, X. Peng, Z. Liu, E. Li and Y. Hu, “A data-driven approach for pipe deformation prediction based on soil properties and weather conditions”, Sustainable Cities and Society, vol.55(102012), pp.1-11, April 2020.
X. Zhao, M. Jia, J. Bin, T. Wang and Z. Liu, “Multiple-Order Graphical Deep Extreme Learning Machine for Unsupervised Fault Diagnosis of Rolling Bearing”, IEEE Transactions on Instrumentation and Measurement, vol.70, pp.1-12, December 2020.
A. Sholehkerdar, J. Tavakoli and Z. Liu, “Theoretical analysis of Tsallis entropy-based quality measure for weighted averaging image fusion”, Information Fusion, vol.58, pp.69-81, June 2020.
M. Khateri, F. Shabanzade, F. Mirzapour, A. Zaji and Z. Liu, “A Variational Approach for Fusion of Panchromatic and Multi-Spectral Images Using a New Spatial-Spectral Consistency Term”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.13, pp.3421-3436, June 2020.
T. Wang, Z. Liu and N. Mrad, “A probabilistic framework for remaining useful life prediction of bearings”, IEEE Transactions on Instrumentation and Measurement, vol.70(3503412), pp.1-12, October 2020.
H. Geirnhas, Z. Liu, X. Chen, W. Li, C. Sensors, G. Brasseur, N. Paulter, W. Recorder, B. Boyer, S. Tilden, T. Linnenbrink, P. Techniques, J. Subcommittee, S. Rapuano, O. A, O. Postolache, J. Scharcanski, G. Giakos, M. Zervakis, M. Siegel, F. Scotti, A. Lay-Ekuakille and G. Xiao, “2020 IEEE IMS Technical Committees”, IEEE Instrumentation & Measurement Magazine, September 2020.
J. Bin, B. Gardiner, E. Li and Z. Liu, “Multi-Source Urban Data Fusion for Property Value Assessment: A Case Study in Philadelphia”, Neurocomputing, vol.404(Sep), pp.70-83, May 2020.
X. Zhao, M. Jia, P. Ding, C. Yang, D. She, L. Zhu and Z. Liu, “A New Intelligent Weak Fault Recognition Framework for Rotating Machinery”, International Journal of Acoustics and Vibration, vol.25(3), pp.461-479, September 2020.
Conference
Z. Bahrami, R. Zhang, R. Rayhana, T. Wang and Z. Liu, “Optimized Deep Neural Network Architectures with Anchor Box optimization for Shipping Container Corrosion Inspection”, 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pp.1328-1333, December 2020.
T. Wang, Z. Liu, X. Zhao, M. Liao and N. Mrad, “Bayesian-Based Method for the Remaining Useful Life and Reliability Prediction of Steel Structure”, 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), pp.1-6, August 2020.
E. P, Y. Zheng, S. Liu and Z. Liu, “Multi-modal Video Fusion for Context-aided Tracking”, 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp.1-8, July 2020.
J. Bin, M. Kang and Z. Liu, “GPU-Accelerated Tensor Decomposition for Moving Object Detection from Multimodal Imaging”, 2020 IEEE Sensors, pp.1-4, October 2020.
L. Xu, Q. Li, J. Jiang, G. Zou, Z. Liu and M. Gao, “Adaptive Spatio-Temporal Regularized Correlation Filters for UAV-based Tracking”, Proceedings of the Asian Conference on Computer Vision, 2020.
Q. Jin and Z. Liu, “Structural Robustness-based SHM Point Arrangement Strategy for In-service Cable-stayed Bridge Subjected to Cable Damage Effect”, 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), pp.1-6, August 2020.
X. Zhao, Z. Liu, T. Wang, J. Bin and M. Jia, “Unsupervised Fault Diagnosis of Machine via Multiple-Order Graphical Deep Extreme Learning Machine”, 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), pp.1-6, August 2020.
R. Rayhana, Y. Jiao, Z. Liu, A. Wu and X. Kong, “Water pipe valve detection by using deep neural networks”, Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems, vol.11382, pp.1138205-1-8, April 2020.
E. Blasch, Z. Liu and Y. Zheng, “Image fusion for context-aided automatic target recognition”, Automatic Target Recognition XXX, vol.11394, pp.113940U-1-12, May 2020.
Close 2020
2019
Journal
G. Bhatnagar, Z. Liu and Q. Jonathan, “Multimodal medical image fusion in NSCT domain”, Big Data in Multimodal Medical Imaging, pp.23, November 2019.
F. Ruffa, C. De, R. Morello and Z. Liu, “Temperature Sensing and Evaluation of Thermal Effects on Battery Packs for Automotive Applications”, IEEE Sensors Journal, vol.19(23), pp.11634-11645, December 2019.
J. Bin, B. Gardiner, Z. Liu and E. Li, “Attention-based multi-modal fusion for improved real estate appraisal: a case study in Los Angeles”, Multimedia Tools and Applications, vol.79(Nov), pp.31163–31184, July 2019.
Q. Jin and Z. Liu, “In-service Bridge SHM Monitoring Point Arrangement with Consideration of Structural Robustness”, Journal of Civil Structural Health Monitoring, vol.9(4), pp.543-554, September 2019.
A. Sholehkerdar, J. Tavakoli and Z. Liu, “In-depth analysis of Tsallis entropy based measures for image fusion quality assessment”, Optical Engineering, vol.58(3), pp.033102-1-16, 2019.
Q. Jin, Z. Liu, J. Bin and W. Ren, “Predictive Analytics of In-Service Bridge Structural Performance from SHM Data Mining Perspective: A Case Study”, Shock and Vibration, vol.2019, pp.1-11, July 2019.
H. Yun, C. Zhang, C. Hou and Z. Liu, “An Adaptive Approach for Ice Detection in Wind Turbine with Inductive Transfer Learning”, IEEE Access, vol.7, pp.122205-122213, July 2019.
J. Xiang, J. Bin and Z. Liu, “Software as a service: the future of NDI data analysis in the cloud”, Insight - Non-Destructive Testing and Condition Monitoring, vol.61(6), pp.341-346, June 2019.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “A fusion of principal component analysis and singular value decomposition based multivariate denoising algorithm for free induction decay transversal data”, Review of Scientific Instruments, vol.90(3), pp.035116, March 2019.
H. Liu, Z. Liu, H. Dong, J. Ge, Z. Yuan, J. Zhu, H. Zhang and X. Zeng, “Recurrent Neural Network-Based Approach for Sparse Geomagnetic Data Interpolation and Reconstruction”, IEEE Access, vol.7, pp.33173-33179, March 2019.
F. Wang, W. Lin, Z. Liu and X. Qiu, “Pressure Signal Enhancement of Slowly Increasing Leaks Using Digital Compensator Based on Acoustic Sensor”, Sensors, vol.19(19), pp.4317, January 2019.
X. Zhao, M. Jia, Z. Liu, P. Ding, C. Yang and L. Zhu, “Fault Diagnosis Framework of Rolling Bearing using Adaptive Sparse Contrative Auto-encoder with Optimized Unsupervised Extreme Learning Machine”, IEEE Access, vol.8, pp.99154-99170, December 2019.
T. Wang, Z. Liu and G. Lu, “Bearing Condition Monitoring based on the Indicator Generated in Time-frequency Domain”, Annual Conference of the PHM Society, vol.11(1), September 2019.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “High-precision sensor tuning of proton precession magnetometer by combining principal component analysis and singular value decomposition”, IEEE Sensors Journal, vol.19(21), pp.9688-9696, July 2019.
H. Liu, Z. Liu, B. Taylor and D. Haobin, “Matching pipeline In-line inspection data for corrosion characterization”, NDT & E International, vol.101, pp.44-52, January 2019.
J. Bin, B. Gardiner, E. Li and Z. Liu, “Peer-Dependence Valuation Model for Real Estate Appraisal”, Data-Enabled Discovery and Applications, vol.3(2), pp.1-11, January 2019.
M. Gao, J. Jiang, G. Zou, V. John and Z. Liu, “RGB-D-Based Object Recognition Using Multimodal Convolutional Neural Networks: A Survey”, IEEE Access, vol.7(1), pp.43110-43136, 2019.
Q. Li, L. Lu, Z. Li, W. Wu, Z. Liu, G. Jeon and X. Yang, “Coupled GAN with Relativistic Discriminators for Infrared and Visible Images Fusion”, IEEE Sensors Journal, vol.0(0), pp.1-22, June 2019.
H. Liu, W. Luo, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Design and implementation of a tuning-matching framework for a high-sensitivity broad band proton precession magnetometer sensing coil”, IEEE Sensors Journal, vol.20(1), pp.127-134, September 2019.
V. John, Z. Liu, S. Mita and Y. Xu, “Stereo vision-based vehicle localization in point cloud maps using multiswarm particle swarm optimization”, Signal, Image and Video Processing, vol.13, pp.805-812, January 2019.
H. Liu, W. Luo, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Design and Implementation of a Tuning-Matching Framework for a High-Sensitivity Broad Band Proton Precession Magnetometer Sensing Coil”, IEEE Sensors Journal, vol.20(1), pp.127-134, September 2019.
G. Wang, Q. Li, L. Wang, Y. Zhang and Z. Liu, “Elderly fall detection with an accelerometer using lightweight neural networks”, Electronics, vol.8(11), pp.1354, November 2019.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Efficient Performance Optimization for the Magnetic Data Readout From a Proton Precession Magnetometer With Low-Rank Constraint”, IEEE Transactions on Magnetics, vol.55(8), pp.1-4, August 2019.
H. Liu, J. Bin, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Adaptive pre-whiten filtering for the free induction decay transversal signal in weak magnetic detection”, Review of Scientific Instruments, vol.90, pp.104502, October 2019.
F. Wang, W. Lin, Z. Liu and X. Qiu, “Pipeline Leak Detection and Location Based on Model-Free Isolation of Abnormal Acoustic Signals”, Energies, vol.12(16), pp.3172-1-18, August 2019.
F. Shabanzade, M. Khateri and Z. Liu, “MR and PET Image Fusion Using Nonparametric Bayesian Joint Dictionary Learning”, IEEE Sensors Letters, vol.3(7), pp.1-4, July 2019.
L. Lu, G. Zhu, X. Yang, K. Zhou, Z. Liu and W. Wu, “Affine Projection Algorithm based High-Order Error Power for Partial Discharge Denoising in Power Cables”, IEEE Transactions on Instrumentation and Measurement, vol.69(4), pp.1821-1832, May 2019.
Conference
Z. Li, J. Yang, Z. Liu, X. Yang, G. Jeon and W. Wu, “Feedback network for image super-resolution”, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.3867-3876, 2019.
X. Peng, K. Siggers and Z. Liu, “Multi-MFL Measurement Assessment using Gaussian Mixture Model”, 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC), pp.529-534, August 2019.
S. Liu, X. Peng and Z. Liu, “Image Quality Assessment through Contour Detection”, 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), pp.1413-1417, June 2019.
G. Wang, Z. Liu and Q. Li, “Fall Detection with Neural Networks”, 2019 IEEE International Flexible Electronics Technology Conference (IFETC), pp.1-7, August 2019.
X. Peng, C. Zhang, U. Anyaoha, K. Siggers and Z. Liu, “Parameterizing magnetic flux leakage data for pipeline corrosion defect retrieval”, 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), pp.2665-2670, June 2019.
U. Anyaoha, X. Peng and Z. Liu, “Concrete performance prediction using boosting smooth transition regression trees (BooST)”, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII, vol.10971, pp.109710I, April 2019.
M. Gao, J. Jiang, L. Ma, S. Zhou, G. Zou, J. Pan and Z. Liu, “Violent crowd behavior detection using deep learning and compressive sensing”, 2019 Chinese Control And Decision Conference (CCDC), pp.5329-5333, June 2019.
E. Blasch, Z. Liu, Y. Zheng, U. Majumder, A. Aved and P. Zulch, “Multisource deep learning for situation awareness”, SPIE Defense + Commercial Sensing, vol.10988, May 2019.
X. Fu, C. Zhang, X. Peng, L. Jian and Z. Liu, “Towards end-to-end pulsed eddy current classification and regression with CNN”, 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp.1-5, May 2019.
G. Zou, G. Fu, X. Peng, Z. Liu and M. Gao, “Multi-supervised CML for Small Sample Low-resolution Image Matching”, 2019 Chinese Automation Congress (CAC), pp.1046-1051, November 2019.
J. Lin, K. Ranslam, F. Shi, M. Figurski and Z. Liu, “Data Migration from Operating EMRs to OpenEMR with Mirth Connect.”, ITCH, pp.288-292, January 2019.
Close 2019
2018
Journal
F. Shi, Y. Liu, Z. Liu and E. Li, “Prediction of pipe performance with stacking ensemble learning based approaches”, Journal of Intelligent & Fuzzy Systems(Preprint), pp.1-11, 2018.
V. John, Z. Liu, S. Mita, C. Guo and K. Kidono, “Real-time road surface and semantic lane estimation using deep features”, Signal, Image and Video Processing, vol.12(6), pp.1133-1140, September 2018.
H. Liu, Z. Liu, S. Liu, Y. Liu, J. Bin, F. Shi and H. Dong, “A nonlinear regression application via machine learning techniques for geomagnetic data reconstruction processing”, IEEE Transactions on Geoscience and Remote Sensing, vol.57(1), pp.128-140, July 2018.
Z. Liu, E. Blasch, G. Bhatnagar, V. John, W. Wu and R. S, “Fusing Synergistic Information from Multi-Sensor Images: An Overview from Implementation to Performance Assessment”, Information Fusion, vol.42, pp.127-145, 2018.
H. Liu, H. Dong, Z. Liu, J. Ge, W. Luo, C. Zhang, Z. Yuan, J. Zhu and H. Zhang, “A comprehensive study on the weak magnetic sensor character of different geometries for proton precession magnetometer”, Journal of Instrumentation, vol.13(09), pp.1-18, September 2018.
H. Liu, H. Dong, J. Ge, Z. Liu, Z. Yuan, J. Zhu and H. Zhang, “Apparatus and method for efficient sampling of critical parameters demonstrated by monitoring an overhauser geomagnetic sensor”, AIP Review of Scientific Instruments, vol.89(12), pp.125109–1–8, November 2018.
Y. Liu, S. Liu, H. Liu, C. Mandache and Z. Liu, “Pulsed Eddy Current Data Analysis for the Characterization of the Second-Layer Discontinuities”, Journal of Nondestructive Evaluation, vol.38(7), pp.8, November 2018.
H. Liu, H. Dong, Z. Liu and G. Jian, “Application of Hilbert-Huang Decomposition to Reduce Noise and Characterize for NMR FID Signal of Proton Precession Magnetometer”, Instruments and Experimental Techniques, vol.61(1), pp.55-64, January 2018.
Z. Liu, N. Meyendorf and N. Mrad, “The role of data fusion in predictive maintenance using digital twin”, AIP Conference Proceedings, vol.1949(1), pp.020023, April 2018.
V. John, A. Boyali, H. Tehrani, K. Ishimaru, M. Konishi, Z. Liu and S. Mita, “Estimation of Steering Angle and Collision Avoidance for Automated Driving using Deep Mixture of Experts”, IEEE Transactions on Intelligent Vehicles, vol.3(4), pp.571-584, December 2018.
Y. Huang, W. Li, M. Gao and Z. Liu, “Algebraic multi-grid based multi-focus image fusion using watershed algorithm”, IEEE Access, vol.6(1), pp.47082-47091, 2018.
Book
Y. Zheng, E. Blasch and Z. Liu, “Multispectral Image Fusion and Colorization”, pp.396, April 2018.
Y. Zheng, E. Blasch and Z. Liu, “Multispectral image fusion and colorization”, vol.481, March 2018.
Z. Liu, N. Meyendorf and N. Mrad, “The role of data fusion in predictive maintenance using digital twin”, vol.1949(1), pp.020023, April 2018.
Conference
C. Zhang, J. Bin and Z. Liu, “Wind turbine ice assessment through inductive transfer learning”, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp.1-6, May 2018.
F. Shi, X. Peng, H. Liu, Y. Hu, Z. Liu and E. Li, “Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods”, Smart Structures and NDE for Industry 4.0, vol.10602, pp.1060207, March 2018.
S. Liu, V. John, E. Blasch, Z. Liu and Y. Huang, “IR2VI: enhanced night environmental perception by unsupervised thermal image translation”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.1153-1160, 2018.
H. Liu, Y. Liu, S. Liu, Z. Liu, J. Ge, H. Song, Z. Yuan, J. Zhu, H. Zhang and H. Dong, “What can machine learning do for geomagnetic data processing? A reconstruction application”, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp.1-6, May 2018.
Q. Jin, J. Bin, W. Ren and Z. Liu, “Structural Performance Analysis and Prediction for In-Service Bridge with SHM Data Mining”, Canadian Society for Civil Engineering (CSCE) 2018 Annual Conference, pp.GC177-1-11, June 2018.
E. Blasch, S. Liu, Z. Liu and Y. Zheng, “Deep Learning Measures of Effectiveness”, NAECON 2018-IEEE National Aerospace and Electronics Conference, pp.254-261, July 2018.
S. Liu, V. John, E. Blasch, Z. Liu and Y. Huang, “IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.1153-1160, 2018.
Close 2018
2017
Journal
F. Wang, W. Lin, Z. Liu, S. Wu and X. Qiu, “Pipeline Leak Detection by Using Time-Domain Statistical Features”, IEEE Sensors Journal, vol.17(19), pp.6431-6442, August 2017.
G. Bhatnagar and Z. Liu, “Multi-sensor fusion based on local activity measure”, IEEE Sensors Journal, vol.17(22), pp.7487-7496, October 2017.
R. Morello, S. Mukhopadhyay, E. Gaura, Z. Liu, D. Slomovitz, S. Ranjan and U. Onyewuchi, “Guest editorial special issue on smart sensors for smart grids and smart cities”, IEEE Sensors Journal, vol.17(23), pp.7594-7595, November 2017.
V. John, Q. Long, Y. Xu, Z. Liu and S. Mita, “Sensor Fusion and Registration of Lidar and Stereo Camera without Calibration Objects”, IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences, vol.100(2), pp.499-509, February 2017.
Z. Liu, E. Blasch and J. Vijay, “Statistical comparison of image fusion algorithms: Recommendations”, Information Fusion, vol.36, pp.251-260, July 2017.
H. Liu, H. Dong, Z. Liu, J. Ge, B. Bai and C. Zhang, “Noise characterization for the FID signal from proton precession magnetometer”, Journal of Instrumentation, vol.12, pp.1-14, July 2017.
H. Liu, H. Dong, Z. Liu, J. Ge, B. Bai and C. Zhang, “Construction of an Overhauser magnetic gradiometer and the applications in geomagnetic observation and ferromagnetic target localization”, Journal of Instrumentation, vol.12(10), pp.T10008, October 2017.
V. John, S. Tsuchizawa, Z. Liu and S. Mita, “Fusion of thermal and visible cameras for the application of pedestrian detection”, Signal, Image and Video Processing, vol.11(3), pp.517-524, March 2017.
L. Zhao, R. Ichise, Z. Liu, S. Mita and Y. Sasaki, “Ontology-based driving decision making: A feasibility study at uncontrolled intersections”, IEICE TRANSACTIONS on Information and Systems, vol.100(7), pp.1425-1439, July 2017.
Conference
H. Liu, S. Liu, Z. Liu, N. Mrad and H. Dong, “Prognostics of damage growth in composite materials using machine learning techniques”, 2017 IEEE International Conference on Industrial Technology (ICIT), pp.1042-1047, March 2017.
V. John, Y. Xu, S. Mita, Q. Long and Z. Liu, “Registration of GPS and stereo vision for point cloud localization in intelligent vehicles using particle swarm optimization”, International Conference on Swarm Intelligence, pp.209-217, July 2017.
J. Bin, S. Tang, Y. Liu, G. Wang, B. Gardiner, Z. Liu and E. Li, “Regression model for appraisal of real estate using recurrent neural network and boosting tree”, 2017 2nd IEEE international conference on computational intelligence and applications (ICCIA), pp.209-213, September 2017.
F. Shi, Z. Liu and E. Li, “Prediction of pipe performance with ensemble machine learning based approaches”, 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC), pp.408-414, August 2017.
Z. Liu and H. Liu, “Experimenting capacitive sensing technique for structural integrity assessment”, 2017 IEEE International Conference on Industrial Technology (ICIT), pp.922-927, March 2017.
Book Chapter
R. Qi, C. Feng, Z. Liu and N. Mrad, “Blockchain-powered internet of things, e-governance and e-democracy”, pp.509-520, 2017.
R. Morello, S. C, Z. Liu, D. Slomovitz and S. Ranjan, “Advances on sensing technologies for smart cities and power grids: A review”, vol.17(23), pp.7596-7610, August 2017.
Book
S. Liu, V. John and Z. Liu, “On the Prospects of Using Deep Learning for Surveillance and Security Applications”, vol.31, pp.218, 2017.
Close 2017
2016
Conference
Z. Liu, G. Monte and V. Huang, “ISO/IEC/IEEE P21451-001 standard for signal treatment of sensory data”, 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), pp.766-771, June 2016.
L. Zhao, R. Ichise, Y. Sasaki, Z. Liu and T. Yoshikawa, “Fast decision making using ontology-based knowledge base”, 2016 IEEE Intelligent Vehicles Symposium (Gothenburg, Sweden, June 19-22, 2016), pp.173-178, 2016.
Journal
Y. Song, W. Wu, Z. Liu, X. Yang, K. Liu and W. Lu, “An Adaptive Pansharpening Method by Using Weighted Least Squares Filter”, IEEE Geoscience and Remote Sensing Letters, vol.13(1), pp.18-22, January 2016.
B. Qia, V. John, Z. Liu and S. Mita, “Pedestrian detection from thermal images: A sparse representation based approach”, Infrared Physics & Technology, vol.76, pp.157-167, May 2016.
Close 2016
2015
Conference
V. John, S. Mita, Z. Liu and B. Qi, “Pedestrian detection in thermal images using adaptive fuzzy C-means clustering and convolutional neural networks”, 2015 14th IAPR international conference on machine vision applications (MVA), pp.246-249, May 2015.
V. John, Q. Long, Z. Liu and S. Mita, “Automatic Calibration and Registration of Lidar and Stereo Camera without Calibration Objects”, IEEE International Conference on Vehicular Electronics and Safety, 2015.
Z. Liu, R. Morello and W. Wu, “Experiments on battery capacity estimation”, 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, pp.863-868, May 2015.
V. John, Z. Liu, C. Guo, S. Mita and K. Kidono, “Real-time lane estimation using deep features and extra trees regression”, Image and Video Technology, pp.721-733, November 2015.
Journal
G. Bhatnagar and Z. Liu, “A novel image fusion framework for night-vision navigation and surveillance”, Signal, Image and Video Processing, vol.9(1), pp.165-175, December 2015.
V. John, K. Yoneda, Z. Liu and S. Mita, “Saliency Map Generation by the Convolutional Neural Network for Real-Time Traffic Light Detection Using Template Matching”, Computational Imaging, IEEE Transactions on, vol.1(3), September 2015.
G. Bhatnagar, Q. Jonathan and Z. Liu, “A new contrast based multimodal medical image fusion framework”, Neurocomputing, vol.157, pp.143-152, June 2015.
W. Wu, Z. Liu and Y. He, “Classification of defects with ensemble methods in the automated visual inspection of sewer pipes”, Pattern Analysis and Applications, vol.18(2), pp.263-276, May 2015.
Book Chapter
Z. Liu, H. Ukida, K. Niel and P. Ramuhalli, “Industrial inspection with open eyes: Advance with machine vision technology”, pp.1-37, 2015.
Book
Z. Liu, H. Ukida, P. Ramuhalli and K. Niel, “Integrated Imaging and Vision Techniques for Industrial Inspection”, pp.1-541, 2015.
Close 2015