Personal Information
教授 Supervisor of Doctorate Candidates Supervisor of Master's Candidates
Paper Publications
- Generalized zero-shot domain adaptation with target unseen class prototype learning:NEURAL COMPUTING & APPLICATIONS.2022, Vol.34, No.20,pp17793-17807, WOS:000805925400002, ISSN :0941-0643
- An active unseen sample selection framework for generalized zero-shot classification:INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2022,Vol.13,No.8,pp：2119-2134.
- Partial Label Dimensional Reduction via Semantic Difference Information and Manifold Regularization:INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 31(02),2022,DOI 10.1142/S0218213022500257
- Bias alleviating generative adversarial network for generalized zero-shot classification:Image and Vision Computing .2021,Vol.105,WOS号：WOS:000611984800011
- Low-rank embedded orthogonal subspace learning for zero-shot classification:Journal of Visual Communication and Image Representation (2021): 102981
- Generalized zero-shot classification via iteratively generating and selecting unseen samples:Signal Processing: Image Communication, 2021.92(3):116115
- RSU-Assisted Traffic-Aware Routing Based on Reinforcement Learning for Urban Vanets:IEEE Access, 2020, Vol. 8:5733-5748. WOS:000524645300001
- Learning discriminative and meaningful samples for generalized zero shot classification:Signal Processing: Image Communication, 2020, 87:115920.
- Zero shot Learning Based on Class Visual Prototypes and Semantic Consistency:Pattern Recognition Letters, 2020. Vol.135,,pp：368-374.
- Learning domain invariant unseen features for generalized zero-shot classification:Knowledge-Based Systems, 2020, Vol.206, WOS:000571534300003
- Zero shot learning by partial transfer from source domain with L2,1 norm constraint:Journal of Visual Communication and Image Representation, 2018, 58: 701-711.
- Prototype adjustment for zero shot classification:Signal Processing: Image Communication. 2019, 74: 242-252.
- Reinforcement Learning Based Mobility Adaptive Routing for Vehicular Ad-Hoc Networks:Wireless Personal Communications, 2018, 101(4): 2143-2171.
- Learning unseen visual prototypes for zero-shot classification:Knowledge-Based Systems, 2018, 160: 176-187
- Image classification by semisupervised sparse coding with confident unlabeled samples:Journal of Electronic Imaging, 2017, 26(5): 053013.
- Multi-label local discriminative embedding:Journal of Systems Engineering and Electronics, Vol. 28, No. 5, October 2017, pp.1009– 1018
- Clustered Intrinsic Label Correlations for Multi-label Classification:Expert Systems with Applications, 2017, 81: 134-146.
- Domain adaptation from RGB-D to RGB images:Signal Processing, 2017, 131: 27-35.
- Learning Coupled Classifiers with RGB images for RGB-D object recognition[J]:Pattern Recognition, 2017, 61: 433-446.
- Learning Coupled Classifiers with RGB images for RGB-D object recognition[J]:Pattern Recognition， 2017, 61: 433-446.
- Li, Xiao^Fang, Min^Zhang, Ju-Jie^Wu, Jinqiao,Sample selection for visual domain adaptation via sparse coding:SIGNAL PROCESSING-IMAGE COMMUNICATION,2016,44:92-100
- Fang, Min ; Groen, Frans C.A. ,Collaborative multi-agent reinforcement learning based on experience propagation:Journal of Systems Engineering and Electronics,2013,24(4):683-689
- Zhang, Ju-Jie; Fang, Min; Wang, Hongchun; Li, Xiao,Dependence maximization based label space dimension reduction for multi-label classification:ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2015,45:453-463
- Li, Xiao ; Fang, Min ; Zhang, Ju-Jie ; Wu, Jinqiao ,Learning Coupled Classifiers with RGB images for RGB-D object recognition:Pattern Recognition,2017,61:433-446
- Zhang, Ju-Jie^Fang, Min^Wu, Jin-Qiao^Li, Xiao,Robust label compression for multi-label classification:KNOWLEDGE-BASED SYSTEMS,2016,107:32-42
- Zhang, Ju-Jie; Fang, Min; Li, Xiao,Multi-label learning with discriminative features for each label:NEUROCOMPUTING,2015,154:305-316
- Li, Xiao ; Fang, Min ; Zhang, Ju-Jie ; Wu, Jinqiao ,Domain adaptation from RGB-D to RGB images:Signal Processing,2017,131:27-35
- Li, Xiao; Fang, Min; Wang, Hongchun; Zhang, Ju-Jie,Supervised transfer kernel sparse coding for image classification:PATTERN RECOGNITION LETTERS,2015,68:27-33
- Li, Xiao; Fang, Min; Zhang, Ju-Jie,Projected Transfer Sparse Coding for cross domain image representation:JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2015,33:265-272
- Fang, Min; Guo, Yong; Zhang, Xiaosong; Li, Xiao,Multi-source transfer learning based on label shared subspace:PATTERN RECOGNITION LETTERS,2015,51:101-106
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