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BIOGRAPHY
Welcome to visit Wujie Zhou's Homepage!
個(gè)人簡(jiǎn)介：
周武杰，教授，博士后，碩士生導(dǎo)師，浙江省省級(jí)人才，浙江省電子學(xué)會(huì)理事，IEEE Senior Member，CCF Senior Member，通信學(xué)會(huì)高級(jí)會(huì)員，CSIG/CAAI/CAA Member，CAA模式識(shí)別與機(jī)器智能專委會(huì)委員，CSIG視覺大數(shù)據(jù)專委會(huì)委員，CCF多媒體技術(shù)專委會(huì)委員，CCF Yocsef 杭州AC委員，CAAI青工委委員。2012年入選“青年骨干教師”，2015年入選“優(yōu)秀青年教師資助計(jì)劃”，2016年入選“科大青年英才”，2022年-2024年連續(xù)3年入選斯坦福大學(xué)發(fā)布的全球前2%頂尖科學(xué)家榜單（人工智能與圖像處理領(lǐng)域），2024年入選“科大領(lǐng)軍人才”，2024年入選浙江省高層次人才特殊支持計(jì)劃“萬(wàn)人計(jì)劃”青年拔尖人才。浙江大學(xué)博士后（導(dǎo)師：虞露），國(guó)家留學(xué)基金委公派新加坡南洋理工大學(xué)訪問學(xué)者（導(dǎo)師：Weisi Lin, IEEE Fellow），浙江大學(xué)訪問學(xué)者（導(dǎo)師：楊易）。主要從事人工智能大模型、深度學(xué)習(xí)、機(jī)器視覺與模式識(shí)別、圖像處理等方面的研究；近幾年以第一作者在TIP、TNNLS、TCSVT、TMM、TCAS-I、TII、TITS、JSTSP、TSMC、TBC、TGRS、IEEE IoT Journal、TASE、TAI、TCI、TIM、MIS、TCDS、TETCI、TIV、TBDATA、IEEE Sensors Journal、JSTARS、PR、Information Fusion和中國(guó)科學(xué)等國(guó)際權(quán)威SCI期刊或核心期刊上發(fā)表學(xué)術(shù)論文100多篇，其中SCI收錄70多篇（中科院一區(qū)48篇, IEEE Journal/Transactions/Magazine 61篇，ESI熱點(diǎn)論文/高被引論文10多篇，10余篇論文入選TIP、TCSVT、TMM、MIS和TETCI 等期刊Top 50 Popular Articles），H指數(shù) (h-index)39 (Google Scholar)，被引頻次總計(jì)5300+ (Google Scholar))；申請(qǐng)國(guó)家發(fā)明專利70多項(xiàng)，授權(quán)50多項(xiàng)，多項(xiàng)已轉(zhuǎn)讓投產(chǎn)；第一完成人獲浙江省自然科學(xué)獎(jiǎng)1項(xiàng)，參與獲市科學(xué)技術(shù)獎(jiǎng)1項(xiàng)，浙江省青年科技工作者優(yōu)秀論文獎(jiǎng)1項(xiàng)；擔(dān)任國(guó)家基金通訊評(píng)審專家，浙江省科技專家?guī)鞂＜?，廣東省基金項(xiàng)目評(píng)審專家；擔(dān)任TIP、TNNLS、TCSVT、TCYB、TMM、TBC、JSTSP、TSMC、SPL等國(guó)外權(quán)威SCI期刊稿件評(píng)審人。目前，主持國(guó)家自然科學(xué)基金2項(xiàng)（面上和青年各1項(xiàng))，省自然科學(xué)基金3項(xiàng)（重點(diǎn)、一般和青年各1項(xiàng)），中國(guó)博士后基金1項(xiàng)，企業(yè)重大橫向課題3項(xiàng)，重中之重實(shí)驗(yàn)室開放基金2項(xiàng)和教育廳科研項(xiàng)目1項(xiàng)。指導(dǎo)學(xué)生獲中國(guó)服務(wù)外包創(chuàng)新創(chuàng)業(yè)大賽二等獎(jiǎng)1項(xiàng)。
E-mail: wujiezhou@163.com
微信號(hào)：zwjzust （歡迎加微信交流）
招收研究生（含聯(lián)合培養(yǎng)、轉(zhuǎn)專業(yè)等）:
視覺智能感知與理解實(shí)驗(yàn)室(中央支持地方高校改革發(fā)展專項(xiàng)資助建設(shè)，項(xiàng)目編號(hào)：303011-2019-0008)招收碩士研究生（學(xué)碩：先進(jìn)制造與信息化，專碩：電子信息、應(yīng)用統(tǒng)計(jì)），主要研究方向：人工智能大模型、深度學(xué)習(xí)、機(jī)器視覺與模式識(shí)別、圖像處理、視覺大數(shù)據(jù)統(tǒng)計(jì)與應(yīng)用。共計(jì)培養(yǎng)了40多名研究生（所有研究生均按時(shí)畢業(yè)）。其中，20多名畢業(yè)生選擇進(jìn)入長(zhǎng)三角人工智能相關(guān)企業(yè)工作，另有20多名畢業(yè)生（絕大部分為專碩學(xué)生）攻讀國(guó)內(nèi)外名校的博士學(xué)位，如北京大學(xué)、University of Liverpool、University of North Texas、University of Technology Sydney、University of Georgia、Oregon State University、武漢大學(xué)、同濟(jì)大學(xué)、南開大學(xué)、北京理工大學(xué)、湖南大學(xué)、華南理工大學(xué)、北京郵電大學(xué)、西北大學(xué)、南京理工大學(xué)、南昌大學(xué)、上海大學(xué)、湘潭大學(xué)和寧波大學(xué)等高校。目前，指導(dǎo)的研究生中14名獲國(guó)家獎(jiǎng)學(xué)金（獎(jiǎng)金2萬(wàn)/人），5名獲卓越學(xué)子獎(jiǎng)學(xué)金（獎(jiǎng)金3萬(wàn)/人），1名獲校“大學(xué)生年度人物”，2篇論文獲校優(yōu)秀碩士論文。預(yù)加入實(shí)驗(yàn)室請(qǐng)發(fā)個(gè)人簡(jiǎn)歷和本科成績(jī)（可系統(tǒng)截圖）到E-mail: wujiezhou@163.com
實(shí)驗(yàn)室"卓越學(xué)子"視頻（視頻中第2位同學(xué)--吳君委）：https://mp.weixin.qq.com/s/vYokNzDeHmtVKmIkOcpnnw
實(shí)驗(yàn)室"大學(xué)生年度人物"（視頻中第8位同學(xué)--劉勁夫）：https://mp.weixin.qq.com/s/ALDUnCtIs8dbnKoGHvDd3Q
實(shí)驗(yàn)室”卓越學(xué)子”簡(jiǎn)介（范曉敏）https://mp.weixin.qq.com/s/hJ9owybCYjAHLWCy5O4BLw
獎(jiǎng)項(xiàng)榮譽(yù)
1、認(rèn)知啟發(fā)式視覺質(zhì)量評(píng)價(jià)的理論與方法，2023年度浙江省自然科學(xué)獎(jiǎng)三等獎(jiǎng)，第一完成人
2、立體視覺信息隱藏相關(guān)理論與關(guān)鍵技術(shù)，2019年度寧波市科學(xué)技術(shù)獎(jiǎng)二等獎(jiǎng)，第三完成人
科研項(xiàng)目
1、國(guó)家自然科學(xué)基金面上項(xiàng)目，62371422 ，視覺認(rèn)知啟發(fā)式雙目視覺顯著性物體檢測(cè)模型研究，主持
2、國(guó)家自然科學(xué)基金青年項(xiàng)目，61502429 ，基于數(shù)據(jù)挖掘與感知分析的非對(duì)稱失真視覺質(zhì)量評(píng) 價(jià)模型研究，主持
3、國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目，2022YFE0196000，數(shù)據(jù)和知識(shí)聯(lián)合驅(qū)動(dòng)城市易腐垃圾炭化與綠色可持續(xù)利用的關(guān)鍵技術(shù)及應(yīng)用，主研
4、浙江省自然科學(xué)基金重點(diǎn)項(xiàng)目，ZCLZ25F0202，面向智慧城市視頻監(jiān)控系統(tǒng)的多模態(tài)人群密度估計(jì)關(guān)鍵技術(shù)研究，主持
5、浙江省自然科學(xué)基金一般項(xiàng)目，LY18F020012，基于雙目視覺機(jī)理挖掘的立體視頻質(zhì)量評(píng)價(jià)模型研究，主持
6、浙江省自然科學(xué)基金青年項(xiàng)目，LQ15F020010，基于立體感知特性分析的非對(duì)稱失真視覺質(zhì)量客觀評(píng)價(jià)模型研究，主持
7、中國(guó)博士后基金面上項(xiàng)目，2015M581932 ，基于視覺感知挖掘的非對(duì)稱失真視覺質(zhì)量評(píng)價(jià)模型， 主持
8、企業(yè)委托項(xiàng)目，2020KJ073，智慧海洋漁船信息智能化管理系統(tǒng)開發(fā)項(xiàng)目，主持
9、企業(yè)委托項(xiàng)目，2021KJ005，生活垃圾投放智能化監(jiān)管系統(tǒng)開發(fā)，主持
10、企業(yè)委托項(xiàng)目，2021KJ130 ，基于機(jī)器視覺的晶振相關(guān)產(chǎn)品缺陷圖像識(shí)別算法，主持
代表作（中科院一區(qū)或IEEE Trans.或CCF A類）
[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類)
[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類)
[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類)
[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類)
[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), 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, doi: 10.1109/TCSI.2024.3521933.
[17] 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.
[18] 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.
[19] 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, doi: 10.1109/TNNLS.2024.3479453.
[20] 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.
[21] 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.
[22] 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.
[23] 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.
[24] 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.
[25] 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.
[26] 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.
[27] 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.
[28] 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.
[29] 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.
[30] 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.
[31] 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.
[32] 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.
[33] 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.
[34] 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.
[35] 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.
[36] 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.
[37] 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.
[38] 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.
[39] 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, doi: 10.1109/JIOT.2025.3537281.
[40] 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.
[41] 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.
[42] 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.
[43] 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.
[44] 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.
[45] 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.
[46] 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.
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[52] 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.
[53] 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.
[54] 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.
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[56] 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, doi: 10.1109/TETCI.2024.3442848.
[57] 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.
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[59] 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.
[60] 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.
[61] 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.
[62] 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類)
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[64] 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.
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[67] 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.
[68] 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.
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[70] 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.
[71] 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.
[72] 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.
[73] 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.
[74] 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.
[75] 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.
[76] 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.
[77] 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.
[78] 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.
[79] 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.
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[81] 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.
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[84] 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.
[85] H. Zhang (研究生), X. Ran and W. Zhou*, "Self-Knowledge Distillation-Based Staged Extraction and Multiview Collection Network for RGB-D Mirror Segmentation," IEEE Signal Processing Letters, vol. 31, pp. 1029–1033, 2024.
[86] 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.
[87] X. Guo (研究生), W. Zhou*, T. Liu, “Contrastive Learning-Based Knowledge Distillation for RGB-Thermal Urban Scene Semantic Segmentation,” Knowledge-Based Systems, vol. 292, 2024, Art. no. 111588.
[88] X. Guo (研究生), W. Zhou*, T. Liu, “Multilevel attention imitation knowledge distillation for RGB-thermal transmission line detection,” Expert Systems with Applications, vol. 260, 2025, Art. no. 125406.
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[90] 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.
[91] 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.
[92] 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.
[93] E. Yang (研究生), W. Zhou*, X., Qian, J. Lei, and L. Yu, “DRNet: Dual-stage refinement network with boundary inference for RGB-D semantic segmentation of indoor scenes,” Engineering Applications of Artificial Intelligence, vol. 125, 2023, Art. no. 106729.
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