ZHOU Wu-Jie 

Brief Education and Work Background

Ningbo University, Doctor of Information and Communication Engineering, Sep 2010-Aug 2014

Zhejiang University, Postdoc of Information and Communication Engineering, Dec 2014-Dec 2016

Nanyang Technological University, visiting scholar, Dec 2022-Dec 2023

Zhejiang University of Science and Technology, Computer Science and Technology (Master Tutor), Nov 2016-Present

Zhou Wujie, born in September 1983, is a professor/postdoctoral fellow, master's supervisor, director of the Zhejiang Electronic Society, IEEE Senior Member, senior member of the Communication Society, CCF Member, member of the Chinese Artificial Intelligence Society, and responsible for the first-class discipline B direction of "Computer Science and Technology" in Zhejiang Province. In 2012, he was selected as a "young backbone teacher", in 2015, he was selected for the "Outstanding Young Teacher Support Program", in 2016, he was selected as a "Young Talent of Keda", and in 2022 and 2023, he was consecutively selected for the global top 2% list of top scientists released by Stanford University. He obtained his postdoctoral degree in Information and Communication Engineering from Zhejiang University, and was a visiting scholar at Nanyang Technological University in Singapore funded by the China Scholarship Council (supervisor: Weisi Lin, Fellow IEEE). He is mainly engaged in research on artificial intelligence and deep learning, machine vision and pattern recognition, image processing, etc.; in recent years, as the first author, he has published more than 70 academic papers in international authoritative SCI journals or core journals such as AAAI, TIP, TNNLS, TCSVT, TMM, TII, TITS, JSTSP, TSMC, TBC, TGRS, IEEE IoT Journal, TASE, TCI, TIM, MIS, TCDS, TETCI, TIV, IEEE Sensors Journal, JSTARS, PR, Information Fusion, and Science in China, among which more than 60 are indexed by SCI (32 in the first zone of the Chinese Academy of Sciences, 43 in IEEE Journal/Transactions/Magazine, 32 in CAA-A class journals, 31 in CCF-A and B class journals/conferences, 6 in ESI hot papers, and more than 10 papers selected as Top 50 Popular Articles in journals such as TIP, TCSVT, TMM, MIS, and TETCI), with an H index of 29 (Google Scholar) and a total citation frequency of over 3150+ (Google Scholar); he has applied for more than 70 national invention patents, with more than 50 authorized, several of which have been transferred for production; he has won the second prize of the municipal science and technology award, and the outstanding paper award for young science and technology workers in Zhejiang Province; he serves as a communication review expert for the National Natural Science Foundation and an expert in the Zhejiang Provincial Science and Technology Expert Database, as well as a fund project review expert in Guangdong Province; he also serves as a manuscript reviewer for authoritative foreign SCI journals such as TIP, TNNLS, TCSVT, TCYB, TMM, TBC, JSTSP, TSMC, and SPL. At present, he is leading 2 National Natural Science Foundation projects (one general and one youth), 2 provincial natural science foundation projects, 1 China Postdoctoral Science Foundation project, 3 major cross-cutting projects of enterprises, 2 open fund projects of key laboratories, and 1 research project of the Education Department. Under his guidance, students have won one second prize in the China Service Outsourcing Innovation and Entrepreneurship Competition.

E-mail: wujiezhou@163.com

Homepage: https://www.scholat.com/zhouwujie

Main Research Interests
Artificial intelligence and deep learning, machine vision and pattern recognition, image processing

Main Research Projects

At present, he is leading 3 National Natural Science Foundation projects (two general and one youth), 3 provincial natural science foundation projects, 1 China Postdoctoral Science Foundation project, 3 major cross-cutting projects of enterprises, 2 open fund projects of key laboratories, and 1 research project of the Education Department.

Main Published Papers

[1] W. Zhou*(周武杰), J. Liu, J. Lei, L. Yu and J.-N. Hwang, “GMNet: Graded-Feature Multilabel-Learning Network for RGB-Thermal Urban Scene Semantic Segmentation,” IEEE Transactions on Image Processing, vol. 30, pp. 7790–7802, 2021. (CCF A类)

[2] W. Zhou*(周武杰), Y. Zhu*, J. Lei, R. Yang, L. Yu, “LSNet: Lightweight Spatial Boosting Network for Detecting Salient Objects in RGB-Thermal Images,” IEEE Transactions on Image Processing, vol. 32, pp. 1329–1340, 2023. (CCF A类)

[3] W. Zhou(周武杰), F. Sun, Q. Jiang, R. Cong, J.-N. Hwang, “WaveNet: Wavelet Network with Knowledge Distillation for RGB-T Salient Object Detection,” IEEE Transactions on Image Processing, vol. 32, pp. 3027–3039, 2023. (CCF A类)

[4] W. Zhou*(周武杰), L. Yu, Y. Zhou, W. Qiu, M.-W. Wu, and T. Luo, “Local and Global Feature Learning for Blind Quality Evaluation of Screen Content and Natural Scene Images,” IEEE Transactions on Image Processing, vol. 27, no. 5, pp. 2086–2095, May 2018. (CCF A类)

[5] W. Zhou*(周武杰), Y. Zhu, J. Lei, J. Wan, and L. Yu, “CCAFNet: Crossflow and cross-scale adaptive fusion network for detecting salient objects in RGB-D images,” IEEE Transactions on Multimedia, vol. 24, pp. 2192–2204, 2022.

[6] W. Zhou*(周武杰), J. Wu, J. Lei, J.-N. Hwang and L. Yu, “Salient Object Detection in Stereoscopic 3D Images Using a Deep Convolutional Residual Autoencoder,” IEEE Transactions on Multimedia, vol. 23, pp. 3388–3399, 2021.

[7] W. Zhou*(周武杰), X. Lin, J. Lei, L. Yu and J.-N. Hwang, “MFFENet: Multiscale Feature Fusion and Enhancement Network for RGB–Thermal Urban Road Scene Parsing,” IEEE Transactions on Multimedia, vol. 24, pp. 2526–2538, 2022.

[8] W. Zhou*(周武杰), E. Yang, J. Lei, J. Wan, and L. Yu, “PGDENet: Progressive Guided Fusion and Depth Enhancement Network for RGB-D Indoor Scene Parsing,” IEEE Transactions on Multimedia, vol. 25, pp. 3483–3494, 2023.

[9] W. Zhou*(周武杰), L. Yu, “Binocular Responses for No-Reference 3D Image Quality Measurement,” IEEE Transactions on Multimedia, vol. 16, no. 6, pp. 1077–1084, 2016.

[10] W. Zhou*(周武杰), Y. Cai, L. Zhang, W. Yan and L. Yu, "UTLNet: Uncertainty-aware Transformer Localization Network for RGB-Depth Mirror Segmentation," IEEE Transactions on Multimedia, vol. 26, pp. 4564–4574, 2024.

[11] W. Zhou*(周武杰), Q. Guo, J. Lei, L. Yu and J.-N. Hwang, “ECFFNet: Effective and Consistent Feature Fusion Network for RGB-T Salient Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 3, pp. 1224–1235, March 2022.

[12] W. Zhou*(周武杰), H. Zhang, W. Yan, and W. Lin, “MMSMCNet: Modal Memory Sharing and Morphological Complementary Networks for RGB-T Urban Scene Semantic Segmentation,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 33, no. 12, pp. 7096–7108, Dec. 2023.

[13] W. Zhou (周武杰), J. Hong, W. Yan and Q. Jiang, "Modal Evaluation Network via Knowledge Distillation for No-Service Rail Surface Defect Detection," IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 5, pp. 3930–3942, May 2024.

[14] W. Zhou (周武杰), B. Jian, X. Dong and Q. Jiang, “DGPINet-KD: Deep Guided and Progressive Integration Network with Knowledge Distillation for RGB-D Indoor Scene Analysis,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 9, pp. 7844–7855, Sept. 2024.

[15] W. Zhou (周武杰), H. Wu and Q. Jiang, “MDNet: Mamba-Effective Diffusion-Distillation Network for RGB-Thermal Urban Dense Prediction,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 35, no. 4, pp. 3222–3233, April 2025.

[16] W. Zhou (周武杰), Z. Ju, R. Cong and W. Yan, "RCNet: Dual-Network Resonance Collaboration via Mutual Learning for RGB-D Road Defect Detection," IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2025.3617769.

[17] W. Zhou (周武杰), Y. Wang, and X. Qian, "Knowledge Distillation and Contrastive Learning for Detecting Visible-Infrared Transmission Lines using Separated Stagger Registration Network," IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 72, no. 8, pp. 4140–4152, Aug. 2025.

[18] W. Zhou(周武杰), C. Ji, and M. Fang, “Transmission Line Detection through Bidirectional Guided Registration with Knowledge Distillation,” IEEE Transactions on Industrial Informatics, vol. 20, no. 4, pp. 5671–5682, April 2024.

[19] W. Zhou*(周武杰), Q. Guo, J. Lei, L. Yu and J.-N. Hwang, “IRFR-Net: Interactive Recursive Feature-reshaping Network for Detecting Salient Objects in RGB-D Images,” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 3, pp. 4132–4144, March 2025.

[20] W. Zhou (周武杰), X. Sun, X. Qian, and M. Fang, “Asymmetrical Contrastive Learning Network for No-Service Rail Surface Defect Detection,” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 7, pp. 12469–12482, July 2025.

[21] W. Zhou (周武杰), B. Jian, Y. Liu, and Q. Jiang, “Multiattentive Perception and Multilayer Transfer Network Using Knowledge Distillation for RGB-D Indoor Scene Parsing,” IEEE Transactions on Neural Networks and Learning Systems,  vol. 36, no. 10, pp. 18287–18299, Oct. 2025.

[22] W. Zhou*(周武杰), Y. Lv, J. Lei and L. Yu, “Global and Local-Contrast Guides Content-Aware Fusion for RGB-D Saliency Prediction,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 6, pp. 3641–3649, June 2021.

[23] W. Zhou*(周武杰), T. Gong, J. Lei and L. Yu, “DBCNet: Dynamic Bilateral Cross-Fusion Network for RGB-T Urban Scene-Understanding in Intelligent Vehicles,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 12, pp. 7631–7641, Dec. 2023.

[24] W. Zhou (周武杰), T. Gong, and W. Yan, "Knowledge Distillation SegFormer-Based Network for RGB-T Semantic Segmentation," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 55, no. 3, pp. 2170–2182, March 2025.

[25] W. Zhou*(周武杰), E. Yang, J. Lei, and L. Yu, “FRNet: Feature Reconstruction Network for RGB-D Indoor Scene Parsing,” IEEE Journal of Selected Topics in Signal Processing, vol. 16, no. 4, pp. 677–687, June 2022.

[26] W. Zhou*(周武杰), J. Jin, J. Lei, and L. Yu, “CIMFNet: Cross-layer Interaction and Multiscale Fusion Network for Semantic Segmentation of High-Resolution Remote Sensing Images,” IEEE Journal of Selected Topics in Signal Processing, vol. 16, no. 4, pp. 666–676, June 2022.

[27] W. Zhou*(周武杰), Y. Zhang, W. Yan, L. Ye, “An Efficient RGB-D Indoor Scene-Parsing Solution via Lightweight Multi-flow Intersection and Knowledge Distillation,” IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 3, pp. 336–345, April 2024.

[28] W. Zhou*(周武杰), Y. Pan, L. Y, J. Lei, and L. Yu, “DEFNet: Dual-Branch Enhanced Feature Fusion Network for RGB-T Crowd Counting,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 24540–24549, Dec. 2022.

[29] W. Zhou*(周武杰), Y. Lv, J. Lei, and L. Yu, “Embedded Control Gate Fusion and Attention Residual Learning for RGB–Thermal Urban Scene Parsing,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 5, pp. 4794–4803, May 2023.

[30] W. Zhou*(周武杰), X. Yang, J. Lei, W. Yan and L. Yu, "MC3Net: Multimodality Cross-Guided Compensation Coordination Network for RGB-T Crowd Counting," IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 5, pp. 4156–4165, May 2024.

[31] W. Zhou (周武杰), J. Hong, X. Ran, W. Yan and Q. Jiang, "DSANet-KD: Dual Semantic Approximation Network via Knowledge Distillation for Rail Surface Defect Detection," IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 10, pp. 13849–13862, Oct. 2024.

[32] W. Zhou (周武杰), Y. Cai, F. Qiang, "Morphology-Guided Network via Knowledge Distillation for RGB-D Mirror Segmentation," IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 11, pp. 17382–17391, Nov. 2024.

[33] W. Zhou* (周武杰), J. Jin, J. Lei, and J.-N. Hwang, “CEGFNet: Common Extraction and Gate Fusion Network for Scene Parsing of Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022, Art no. 5405110.

[34] W. Zhou (周武杰), X. Fan, W. Yan, S. Shan, Q. Jiang, and J.-N. Hwang, “Graph Attention Guidance Network with Knowledge Distillation for Semantic Segmentation of Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023, Art no. 4506015.

[35] W. Zhou (周武杰), Y. Li, J. Huang, W. Yan, M. Fang and Q. Jiang, “GSGNet-S*: Graph Semantic Guidance Network via Knowledge Distillation for Optical Remote Sensing Image Scene Analysis,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023, Art no. 4508512.

[36] W. Zhou (周武杰), Y. Li, J. Huang, Y. Liu and Q. Jiang, "MSTNet-KD: Multilevel Transfer Networks Using Knowledge Distillation for the Dense Prediction of Remote-Sensing Images," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024, Art no. 4504612.

[37] W. Zhou (周武杰), P. Yang, W. Qiu and F. Qiang, "STONet-S*: A Knowledge-Distilled Approach for Semantic Segmentation in Remote-Sensing Images," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024, Art no. 4414413.

[38] W. Zhou (周武杰), P. Yang, Y. Liu, R. Cong and Q. Jiang, "Remote Sensing Image Scene Classification via Graph Template Enhancement and Supplementation Network with Dual-Teacher Knowledge Distillation," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1–13, 2024, Art no. 3490559.

[39] W. Zhou (周武杰), P. Yang and Y. Liu, "HLMamba: Hybrid Lightweight Mamba-Based Fusion Network for Dense Prediction of Remote Sensing Images," IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1–11, 2025, Art no. 4414211.

[40] W. Zhou (周武杰), X. Yang, X. Dong, “MJPNet-S*: Multistyle Joint-perception Network with Knowledge Distillation for Drone RGB-Thermal Crowd Density Estimation in Smart Cities,” IEEE Internet of Things Journal, vol. 11, no. 11, pp. 20327–20339, June 2024.

[41] W. Zhou (周武杰), X. Yang, W. Yan and Q. Jiang, “Hybrid Knowledge Distillation for RGB-T Crowd Density Estimation in Smart Surveillance Systems,” IEEE Internet of Things Journal, vol. 12, no. 7, pp. 9276–9289, April1, 2025.

[42] W. Zhou (周武杰), B. Jian and Y. Liu, "Feature Contrast Difference and Enhanced Network for RGB-D Indoor Scene Classification in Internet of Things," IEEE Internet of Things Journal, vol. 12, no. 11, pp. 17610–17621, June, 2025.

[43] W. Zhou (周武杰), Y. Xiao, W. Yan, and L. Yu, “CMPFFNet: Cross-Modal and Progressive Feature Fusion Network for RGB-D Indoor Scene Semantic Segmentation,” IEEE Transactions on Automation Science and Engineering, vol. 21, no. 4, pp. 5523–5533, Oct. 2024.

[44] W. Zhou (周武杰), J. Yang, et al. “RDNet-KD: Recursive Encoder, Bimodal Screening Fusion, and Knowledge Distillation Network for Rail Defect Detection,” IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 2031–2040, 2025.

[45] W. Zhou (周武杰), W. Qiu, M. Wu, “MSNet: Multiple Strategy Network with Bidirectional Fusion for Detecting Salient Objects in RGB-D Images,” IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 4341–4353, 2025.

[46] W. Zhou (周武杰), H. Zhang, Y. Liu and T. Luo, "Enhancing RGB-D Mirror Segmentation with a Neighborhood-Matching and Demand-Modal Adaptive Network using Knowledge Distillation," IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 12679–12692, 2025.

[47] W. Zhou* (周武杰), W. Qiu, M. Wu, “Utilizing Dictionary Learning and Machine Learning for Blind Quality Assessment of 3D Images,” IEEE Transactions on Broadcasting, vol. 63, no. 2, pp. 404–415, June 2017.

[48] W. Zhou* (周武杰), S. Dong, J. Lei, and L. Yu, “MTANet: Multitask-Aware Network with Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding,” IEEE Transactions on Intelligent Vehicles, vol. 8, no. 1, pp. 48–58, Jan. 2023.

[49] W. Zhou (周武杰), S. Dong, M. Fang and L. Yu, "CACFNet: Cross-Modal Attention Cascaded Fusion Network for RGB-T Urban Scene Parsing," IEEE Transactions on Intelligent Vehicles, vol. 9, no. 1, pp. 1919–1929, Jan. 2024.

[50] W. Zhou (周武杰), H. Wu, and Q. Jiang, "MGSGNet-S*: Multilayer Guided Semantic Graph Network via Knowledge Distillation for RGB-Thermal Urban Scene Parsing," IEEE Transactions on Intelligent Vehicles, vol. 10, no. 5, pp. 3543–3559, May 2025.

[51] W. Zhou (周武杰), H. Zhang, and W. Qiu, "Differential Modal Multistage Adaptive Fusion Networks via Knowledge Distillation for RGB-D Mirror Segmentation," IEEE Transactions on Big Data, vol. 11, no. 4, pp. 1959–1969, Aug. 2025.

[52] W. Zhou (周武杰), Y. Li, and Y. Liu, "Asymmetric Dual Encoder Network with Clustering and Mutual Contrast Loss for the Semantic Segmentation of Remote Sensing Images," IEEE Transactions on Big Data, doi: 10.1109/TBDATA.

[53] W. Zhou (周武杰), Y. Wu, F. Qiang and W. Yan, "Lightweight Scope Integration Network for Rail Surface Defect Detection," IEEE Transactions on Big Data, doi: 10.1109/TBDATA.2025.3618444.

[54] W. Zhou (周武杰), Y. Xiao, Y. Liu, and Q. Jiang, “FIMKD: Feature-Implicit Mapping Knowledge Distillation for RGB-D Indoor Scene Semantic Segmentation,” IEEE Transactions on Artificial Intelligence, vol. 5, no. 12, pp. 6488–6499, Dec. 2024.

[55] W. Zhou (周武杰), B. Wang, X. Dong, J. Meng, “Location, Neighborhood, and Semantic Guidance Network for RGB-D Co-Salient Object Detection,” IEEE Transactions on Artificial Intelligence, doi: 10.1109/TAI.2025.3564238.

[56] W. Zhou* (周武杰), J. Lei, T. Luo, “TSNet: Three-stream Self-attention Network for RGB-D Indoor Semantic Segmentation,” IEEE Intelligent Systems, vol. 36, no. 4, pp. 73–78, July-Aug. 2021.

[57] W. Zhou* (周武杰), S. Lv, J. Lei, and L. Yu, “RFNet: Reverse Fusion Network with Attention Mechanism for RGB-D Indoor Scene Understanding,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 2, pp. 598–603, April 2023.

[58] W. Zhou* (周武杰), Y. Zhu, J. Lei, J. Wan, and L. Yu, “APNet: Adversarial-Learning-Assistance and Perceived Importance Fusion Network for All-Day RGB-T Salient Object Detection,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 4, pp. 957–968, Aug. 2022.

[59] W. Zhou* (周武杰), S. Pan, J. Lei, and L. Yu, “TMFNet: Three-Input Multilevel Fusion Network for Detecting Salient Objects in RGB-D Images,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 3, pp. 593–601, June 2022.

[60] W. Zhou (周武杰), G. Xu, “ACENet: Auxiliary Context-Information Enhancement Network for RGB-D Indoor Scene Semantic Segmentation,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 8, no. 2, pp. 1125–1129, April 2024.

[61] W. Zhou (周武杰), T. Gong, "BFTNet: Boundary-Induced Four-Phase Transformer Network for RGB-Thermal Urban Road Scene Parsing," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 9, no. 4, pp. 2703–2712, Aug. 2025.

[62] W. Zhou (周武杰), Y. Wu, J. Meng and X. Dong, "Morphology Recognition Network via Contrastive Distillation for Detecting Rail Surface Defects," IEEE Transactions on Emerging Topics in Computational Intelligence, doi: 10.1109/TETCI.2025.3593905.

[63] W. Zhou* (周武杰), W. Liu, J. Lei, T. Luo, L. Yu, “Deep Binocular Fixation Prediction Using Hierarchical Multimodal Fusion Network,” IEEE Transactions on Cognitive and Developmental Systems, vol. 15, no. 2, pp. 476–486, June 2023.

[64] W. Zhou* (周武杰), J. Lei, Q. Jiang, L. Yu and T. Luo, “Blind Binocular Visual Quality Predictor Using Deep Fusion Network,” IEEE Transactions on Computational Imaging, vol. 6, pp. 883–893, 2020.

[65] W. Zhou* (周武杰), and J. Hong, “FHENet: Lightweight Feature Hierarchical Exploration Network for Real-Time Rail Surface Defect Inspection in RGB-D Images,” IEEE Transactions on Instrumentation and Measurement, vol. 72, 2023, Art no. 5005008.  

[66] W. Zhou (周武杰), C. Ji and M. Fang, “Effective Dual-Feature Fusion Network for Transmission Line Detection,” IEEE Sensors Journal, vol. 24, no. 1, pp. 101–109, Jan. 2024.

[67] W. Zhou* (周武杰), X. Fan, L. Yu, and J. Lei, “MISNet: Multiscale Cross-layer Interactive and Similarity Refinement Network for Scene Parsing of Aerial Images,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 2025–2034, 2023.

[68] W. Zhou* (周武杰), C. Liu, J. Lei, and L. Yu, “Remaking learning: A Lightweight Network for Saliency Redetection on RGB-D Images,” SCIENCE CHINA Information Sciences, vol. 65, no. 5, Art. no. 160107, 2022. (CCF A类)

[69] W. Zhou* (周武杰), S. Dong, C. Xu, Y. Qian, “Edge-aware Guidance Fusion Network for RGB–Thermal Scene Parsing,” in Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), vol. 36, no. 3, pp. 3571–3579, 2022. (CCF A类, 人工智能顶级会议)

[70] W. Zhou*(周武杰), Y. Yue, M. Fang, X. Qian, R. Yang, L. Yu, “BCINet: Bilateral Cross-Modal Interaction Network for Indoor Scene Understanding in RGB-D Images,” Information Fusion, vol. 94, pp. 32–42, 2023.

[71] W. Zhou*(周武杰), Y. Cai, X. Dong, F. Qiang, W. Qiu, “ADRNet-S*: Asymmetric depth registration network via contrastive knowledge distillation for RGB-D mirror segmentation,” Information Fusion, vol. 108, 2024, Art no. 102392.

[72] W. Zhou*(周武杰), L. Yu, Y. Zhou, W. Qiu, M.-W. Wu, Ting Luo, “Blind quality estimator for 3D images based on binocular combination and extreme learning machine,” Pattern Recognition, vol. 71, pp. 207–217, Nov. 2017.

[73] W. Zhou*(周武杰), L. Yu, W. Qiu, Y. Zhou, M. Wu, “Local Gradient Patterns (LGP): an Effective Local Statistical Features Extraction Scheme for No-Reference Image Quality Assessment,” Information Sciences, vol. 397–398, pp. 1–14, Aug. 2017.

[74] W. Zhou (周武杰), Y. Wu, W. Qiu, C. Xu, and F. Qiang, “Effective Bi-decoding Networks for Rail-Surface Defect Detection by Knowledge Distillation,” Applied Soft Computing, vol. 167, 2024, Art. no. 112422.

[75] W. Zhou (周武杰), Y. Xiao, F. Qiang, X. Dong, C. Xu, L. Yu, “AESeg: Affinity-enhanced segmenter using feature class mapping knowledge distillation for efficient RGB-D semantic segmentation of indoor scenes,” Neural Networks, vol. 188, 2025, Art. no. 107438.

[76] S. Dong (研究生), W. Zhou*, C. Xu, and W. Yan, "EGFNet: Edge-aware guidance fusion network for RGB–thermal urban scene parsing," IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 1, pp. 657–669, Jan. 2024.

[77] X. Sun (研究生), W. Zhou* and X. Qian, "Normalized Cyclic Loop Network for Rail Surface Defect Detection Using Knowledge Distillation," IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 11, pp. 16561–16573, Nov. 2024.

[78] Y. Li (研究生), W. Zhou*, “Lightweight and Efficient Multimodal Prompt Injection Network for Scene Parsing of Remote-Sensing Scene Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024, Art no. 4417109.

[79] Z. Tu (研究生), W. Zhou*, X. Qian, "Hybrid Knowledge Distillation Network for RGB-D Co-Salient Object Detection," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 55, no. 4, pp. 2695–2706, April 2025.

[80] Y. Wang (研究生), W. Zhou* and X. Qian, “Transmission Line Detection Through Auxiliary Feature Registration with Knowledge Distillation,” IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 9413–9425, 2025.

[81] Z. Tu (研究生), X. Qian and W. Zhou*, "Efficient RGB-D Co-Salient Object Detection via Modality-Aware Prompting," IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 12911–12921, 2025.

[82] B. Wang (研究生), W. Zhou*, W. Yan, Q. Jiang and R. Cong, “PENet-KD: Progressive Enhancement Network via Knowledge Distillation for Rail Surface Defect Detection,” IEEE Transactions on Instrumentation and Measurement, vol. 72, 2023, Art no. 5032811.

[83] Y. Wu (研究生), F. Qiang, W. Zhou* and W. Yan, "PFCNet: Enhancing Rail Surface Defect Detection With Pixel-Aware Frequency Conversion Networks," IEEE Signal Processing Letters, vol. 32, pp. 606–610, 2025.

[84] P. Yang (研究生), W. Zhou* and Y. Liu, "Frequency-Aware Integrity Learning Network for Semantic Segmentation of Remote Sensing Images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 3398–3409, 2025.

[85] X. Yang (研究生), W. Zhou*, W. Yan, X. Qian, “CAGNet: Coordinated attention guidance network for RGB-T crowd counting,” Expert Systems with Applications, vol. 243, 2024, Art no. 122753.

[86] Z. Tu (研究生), X. Qian, W. Zhou*, "Distilled wave-aware network: Efficient RGB-D co-salient object detection via wave learning and three-stage distillation," Information Sciences, vol. 700, 2025, Art. no. 121855.

[87] X. Fan (研究生), W. Zhou*, X. Qian, W. Yan, “Progressive adjacent-layer coordination symmetric cascade network for semantic segmentation of multimodal remote sensing images,” Expert Systems with Applications, vol. 238, 2024, Art. no. 121999.

[88] B. Wang (研究生), F. Qiang, W. Zhou*, “Hierarchical Cross-Modal multianchor distillation for rail surface defect detection,” Measurement, Doi: 10.1016/j.measurement.2025.117600.

[89] Y. Zhang (研究生), F. Qiang, W. Zhou*, “IIBNet: Inter- and Intra-Information Balance Network with Self-Knowledge Distillation and Region Attention for RGB-D Indoor Scene Parsing,” Expert Systems with Applications, vol. 281, 2025, Art. no. 127670.

[90] C. Ji (研究生), W. Zhou*, J. Lei and L. Ye, "Infrared and Visible Image Fusion via Multiscale Receptive Field Amplification Fusion Network," IEEE Signal Processing Letters, vol. 30, pp. 493–497, 2023.

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[92] Y. Xiao (研究生), J. Meng, F. Qiang, X. Dong and W. Zhou*, "Depth Enhancement Mask Mapping Network With Multi-Teacher Distillation for RGB-D Scene Parsing," IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 20572–20583, 2025

[93] J. Jin (研究生), W. Zhou*, L. Ye, J. Lei, L. Yu, X. Qian, T. Luo, “DASFNet: Dense-Attention–Similarity-Fusion Network for scene classification of dual-modal remote-sensing images,” International Journal of Applied Earth Observation and Geoinformation, vol. 115, 2022, Art. no. 103087.

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[97] Y. Pan (研究生), W. Zhou*, X. Qian, S. Mao, R. Yang, and L. Yu, “CGINet: Cross-modality grade interaction network for RGB-T crowd counting,” Engineering Applications of Artificial Intelligence, vol. 126, 2023, Art. no. 106885.

[98] C. Li (研究生), W. Zhou*, X. Zhou and W. Yan, "Semantic Progressive Guidance Network for RGB-D Mirror Segmentation," IEEE Signal Processing Letters, vol. 31, pp. 2780–2784, 2024.

[99] Y. Zhang (研究生), W. Zhou*, X. Ran and M. Fang, "Lightweight Dual Stream Network With Knowledge Distillation for RGB-D Scene Parsing," IEEE Signal Processing Letters, vol. 31, pp. 855–859, 2024.

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[103] Y. Wang (研究生), X. Qian and W. Zhou*, "Transformer-Prompted Network: Efficient Audio–Visual Segmentation via Transformer and Prompt Learning," IEEE Signal Processing Letters, vol. 32, pp. 516–520, 2025.