Jia Liu（刘嘉）

[DBLP] [GitHub]

Associate Professor School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China. Email：omegaliuj@gmail.com

Biography

Received the B.S. and Ph.D. degrees in electronic engineering from Xidian University in 2013 and 2018, respectively.

My research interests include computational intelligence and image understanding.

Selected Journal Papers

[1] J. Liu, M. Gong, L. Xiao, W. Zhang and F. Liu, “Evolving Connections in Group of Neurons for Robust Learning,” in IEEE Transactions on Cybernetics(IEEE T-Cyb), vol. 52, no. 5, pp. 3069-3082, May 2022.

[2] J. Liu, W. Zhang, F. Liu and L. Xiao, “A Probabilistic Model Based on Bipartite Convolutional Neural Network for Unsupervised Change Detection,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 60, pp. 1-14, Art no. 4701514, 2022.

[3] W. Zhang, L. Jiao*, F. Liu, J. Liu* and Z. Cui, “LHNet: Laplacian Convolutional Block for Remote Sensing Image Scene Classification,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), Accepted, 2022.

[4] W. Zhang, L. Jiao*, F. Liu, S. Yang and J. Liu*, “DFAT: Dynamic Feature-Adaptive Tracking,” in IEEE Transactions on Circuits and Systems for Video Technology(IEEE T-CSVT), Accepted, 2022.

[5] W. Zhang, L. Jiao*, F. Liu, S. Yang and J. Liu*, “Adaptive Contourlet Fusion Clustering for SAR Image Change Detection,” in IEEE Transactions on Image Processing(IEEE T-IP), vol. 31, pp. 2295-2308, 2022.

[6] W. Zhang, L. Jiao*, F. Liu, S. Yang, W. Song and J. Liu*, “Sparse Feature Clustering Network for Unsupervised SAR Image Change Detection,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 60, pp. 1-13, Art no. 5226713, 2022.

[7] W. Zhang, L. Jiao, F. Liu, L. Li, X. Liu and J. Liu, “MBLT: Learning Motion and Background for Vehicle Tracking in Satellite Videos,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 60, pp. 1-15, Art no. 4703315, 2022.

[8] F. Liu, J. Wang, X. Tang, J. Liu, X. Zhang and L. Xiao, “Adaptive Graph Convolutional Network for PolSAR Image Classification,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 60, pp. 1-14, Art no. 5208114, 2022.

[9] J. Liu, W. Zhang, F. Liu and L. Xiao, “Deep Associative Learning for Neural Networks,” in Neurocomputing, vol. 443, pp. 222-234, 2021.

[10] M. Gong, J. Liu, A. K. Qin, K. Zhao and K. C. Tan, “Evolving Deep Neural Networks via Cooperative Coevolution With Backpropagation,” in IEEE Transactions on Neural Networks and Learning Systems(IEEE T-NNLS), vol. 32, no. 1, pp. 420-434, Jan. 2021.

[11] W. Zhang, L. Jiao, Y. Li and J. Liu, “Sparse Learning-Based Correlation Filter for Robust Tracking,” in IEEE Transactions on Image Processing(IEEE T-IP), vol. 30, pp. 878-891, 2021.

[12] F. Liu, X. Tang, X. Zhang, L. Jiao and J. Liu, “Large-Scope PolSAR Image Change Detection Based on Looking-Around-and-Into Mode,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 59, no. 1, pp. 363-378, Jan. 2021.

[13] J. Liu, M. Gong, A. K. Qin and K. C. Tan, “Bipartite Differential Neural Network for Unsupervised Image Change Detection,” in IEEE Transactions on Neural Networks and Learning Systems(IEEE T-NNLS), vol. 31, no. 3, pp. 876-890, March 2020.

[14] J. Liu, M. Gong and H. He, “Deep Associative Neural Network for Associative Memory based on Unsupervised Representation Learning,” in Neural Networks, vol. 113, pp. 41-53, 2019.

[15] M. Gong, H. Li, D. Meng, Q. Miao and J. Liu, “Decomposition-Based Evolutionary Multiobjective Optimization to Self-Paced Learning,” in IEEE Transactions on Evolutionary Computation(IEEE T-EC), vol. 23, no. 2, pp. 288-302, April 2019.

[16] P. Zhang, M. Gong, H. Zhang, J. Liu and Y. Ban, “Unsupervised Difference Representation Learning for Detecting Multiple Types of Changes in Multitemporal Remote Sensing Images,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 57, no. 4, pp. 2277-2289, April 2019.

[17] J. Liu, M. Gong, K. Qin and P. Zhang, “A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images,” in IEEE Transactions on Neural Networks and Learning Systems(IEEE T-NNLS), vol. 29, no. 3, pp. 545-559, March 2018.

[18] J. Liu, M. Gong, Q. Miao, X. Wang and H. Li, “Structure Learning for Deep Neural Networks Based on Multiobjective Optimization,” in IEEE Transactions on Neural Networks and Learning Systems(IEEE T-NNLS), vol. 29, no. 6, pp. 2450-2463, June 2018.

[19] L. Su, M. Gong, P. Zhang, M. Zhang, J. Liu and H. Yang, “Deep Learning and Mapping based Ternary Change Detection for Information Unbalanced Images,” in Pattern Recognition, vol. 66, pp. 213-228, 2017.

[20] M. Gong, H. Li, E. Luo, J. Liu and J. Liu, “A Multiobjective Cooperative Coevolutionary Algorithm for Hyperspectral Sparse Unmixing,” in IEEE Transactions on Evolutionary Computation(IEEE T-EC), vol. 21, no. 2, pp. 234-248, April 2017.

[21] W. Zhao, Z. Wang, M. Gong and J. Liu, “Discriminative Feature Learning for Unsupervised Change Detection in Heterogeneous Images Based on a Coupled Neural Network,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 55, no. 12, pp. 7066-7080, Dec. 2017.

[22] J. Liu, M. Gong, J. Zhao, H. Li and L. Jiao, “Difference Representation Learning using Stacked Restricted Boltzmann Machines for Change Detection in SAR Images,” in Soft Computing, vol. 20, no. 12, pp. 4645-4657, 2016.

[23] M. Gong, P. Zhang, L. Su and J. Liu, “Coupled Dictionary Learning for Change Detection From Multisource Data,” in IEEE Transactions on Geoscience and Remote Sensing(IEEE T-GRS), vol. 54, no. 12, pp. 7077-7091, Dec. 2016.

[24] M. Gong, J. Zhao, J. Liu, Q. Miao and L. Jiao, “Change Detection in Synthetic Aperture Radar Images Based on Deep Neural Networks,” in IEEE Transactions on Neural Networks and Learning Systems(IEEE T-NNLS), vol. 27, no. 1, pp. 125-138, Jan. 2016.

[25] H. Li, M. Gong, Q. Wang, J. Liu and L. Su, “A Multiobjective Fuzzy Clustering Method for Change Detection in SAR Images,” in Applied Soft Computing, vol. 46, pp. 767-777, 2016.

[26] J. Liu, M Gong, Q Miao, L Su, H Li, “Change Detection in Synthetic Aperture Radar Images based on Unsupervised Artificial Immune Systems,” in Applied Soft Computing, vol. 34, pp. 151-163, 2015.

[27] M. Gong, J. Liu, H. Li, Q. Cai and L. Su, “A Multiobjective Sparse Feature Learning Model for Deep Neural Networks,” in IEEE Transactions on Neural Networks and Learning Systems(IEEE T-NNLS), vol. 26, no. 12, pp. 3263-3277, Dec. 2015.

[28] H. Li, M. Gong and J. Liu, “A Local Statistical Fuzzy Active Contour Model for Change Detection,” in IEEE Geoscience and Remote Sensing Letters(GRSL), vol. 12, no. 3, pp. 582-586, March 2015.

Selected Conference Papers

[1] J. Liu, W. Zhang, M. Gong and H. He, “Nucleus Neural Network: A Data-driven Self-organized Architecture,” 2020 International Joint Conference on Neural Networks(IJCNN), pp. 1-8, 2020. (Oral)

[2] W. Zhang, L. Jiao, X. Liu and J. Liu, “Multi-Scale Feature Fusion Network for Object Detection in VHR Optical Remote Sensing Images,” IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium(IGARSS), pp. 330-333, 2019. (Oral)

[3] J. Liu, M. Gong and Q. Miao, “Neuron Learning Machine for Representation Learning,” Thirty-First AAAI Conference on Artificial Intelligence(AAAI), pp. 4961-4962, 2017.

[4] J. Liu, M. Gong and Q. Miao, “Modeling Hebb Learning Rule for Unsupervised Learning,” Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence(IJCAI), pp. 2315-2321, 2017.

[5] H. Li, Jingjing Ma, J. Liu, M. Gong and Mingyang Zhang, “Multi-objective Endmember Extraction for Hyperspectral Images,” 2017 IEEE Congress on Evolutionary Computation(CEC), pp. 458-465, 2017.

[6] M. Zhang, Jingjing Ma, M. Gong, Hao Li and J. Liu, “Memetic Algorithm based Feature Selection for Hyperspectral Images Classification,” 2017 IEEE Congress on Evolutionary Computation(CEC), pp. 495-502, 2017.

[7] P. Zhang, M. Gong, H. Zhang and J. Liu, “DRLnet: Deep Difference Representation Learning Network and An Unsupervised Optimization Framework,” Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence(IJCAI), pp. 3413-3419, 2017.

[8] T. Xie, M. Gong, Z. Tang, Y. Lei, J. Liu and Z. Wang, “Enhancing Evolutionary Multifactorial Optimization based on Particle Swarm Optimization,” 2016 IEEE Congress on Evolutionary Computation(CEC), pp. 1658-1665, 2016.

[9] J. Zhao, M. Gong, J. Liu and L. Jiao, “Deep Learning to Classify Difference Image for Image Change Detection,” 2014 International Joint Conference on Neural Networks(IJCNN), pp. 411-417, 2014.

Honors

西安电子科技大学优秀博士学位论文

陕西省优秀博士学位论文

Services

Reviewer of IEEE T-NNLS/IEEE T-EC/IEEE T-Cyb/…