【近三年主要學術論文】: [1] Yuhao Wang, Xuehu Liu, Pingping Zhang, Hu Lu, Zhengzheng Tu, Huchuan Lu, TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation. Association for the Advancement of Artificial Intelligence, AAAI-2024, To appear in 2024. (CCF-A類) [2] Hu Lu, TingTing Jin,Hui Wei, Michele Nappi,Hu Li, ShaoHua Wan,Soft-orthogonal Constrained Dual-stream Encoder with Self-supervised Clustering Network for Brain Functional Connectivity Data. Expert Systems With Applications, To appear in 2024. (中科院1區)
【2023年】 [1] Hu, Lu, Xuezhang Zou, Pingping Zhang, Learning Progressive Modality-shared Transformers for Effective Visible-Infrared Person Re-identification. Association for the Advancement of Artificial Intelligence 2023, AAAI-2023. (CCF-A類) [2] Ziqiang He, Shaohua Wan, Marco Zappatore, Hu Lu*(通訊). A Similarity Matrix Low-Rank Approximation and Inconsistency Separation Fusion Approach for Multi-View Clustering. IEEE Transactions on Artificial Intelligence. TAI. 2023, DOI: 10.1109/TAI.2023.3271964. [3] Yirui Wu, Lilai Zhang, Zonghua Gu, Hu Lu, Shaohua Wan. Edge-AI-Driven Framework with Efficient Mobile Network Design for Facial Expression Recognition. ACM Transactions on Embedded Computing Systems. 2023, DOI:10.1145/3587038. [4] Chao Chen, Hu Lu*(通訊), Haotian Hong, Hai Wang, Shaohua Wan. Deep Graph Attention Convolution Autoencoder Clustering for Social Network Connection Analysis. TCE, IEEE Transactions on Consumer Electronics. 2023.
【2022年】 [1] Li, H., Wu Y., Hu, H., Lu, H., Lai, Y., Wan, S., Learning Group-Disentangled Representation for Interpretable Thoracic Pathologic Prediction. International Conference on Bioinformatics & Biomedicine 2022, BIBM-2022. (CCF-B類) [2] Ding, S., Wang, H., Lu, H., Nappi, M., & Wan, S. (2022). Two path gland segmentation algorithm of colon pathological image based on local semantic guidance. IEEE journal of biomedical and health informatics, (SCI檢索,Impact factor: 7.021) [3] Chao Chen, Hu Lu*(通訊), Hui Wei, Xia Geng. Deep Subspace Image Clustering Network with Selfexpression and Self-supervision [J]. Applied Intelligence. accepted, 2022, (SCI檢索,Impact factor=5.086) [4] Hu Lu, Chao Chen, Hui Wei, Zhongchen Ma, Ke Jiang, Yingquan Wang. Improved Deep Convolutional Embedded Clustering with Re-selectable Sample Training [J]. Pattern Recognition. Volume 127, 2022, doi : 10.1016/j.patcog.2022.108611. (SCI檢索,Impact factor=7.74)[source code] [5] Hu Lu*(通訊), Tingting Jin. Dual-Stream Encoder Neural Networks with Spectral Constraint for Clustering Functional Brain Connectivity Data [J]. Neural Computing and Applications. 2022, doi : 10.1007/s00521-022-07122-7. (SCI檢索,Impact factor=5.606)[source code] [6] Yingquan Wang, Ke Jiang, Hu Lu*(通訊), Ziheng Xu, Gaojian Li, Chao Chen, Xia Geng. Encoder-Decoder Assisted Image Generation for Person re-identification[J]. Multimedia Tools and Applications. 2022, doi : 10.1007/s11042-022-11907-2. (SCI檢索,Impact factor=2.757)
【2021年】 [1] Yingquan Wang, Pingping Zhang, Shang Gao, Xia Geng, Hu Lu*(通訊), Dong Wang. Pyramid Spatial-Temporal Aggregation for Video-based Person Re-Identification. Proceedings of the IEEE International Conference on Computer Vision, v 2021-October, p12026-12035, Proceedings - 2021 International Conference on Computer Vision, ICCV 2021. (CCF-A類) [2] Hu Lu*(通訊), Saixiong Liu, Hui Wei, Chao Chen, Xia Geng, Deep multi-kernel auto-encoder network for clustering brain functional connectivity data. Neural Networks. Volume 135, 2021, pp 148-157. DOI: 10.1016/j.neunet.2020.12.005. (SCI檢索,Impact factor=8.05) [3] Thomas Martial Epalle*, Yuqing Song, Zhe Liu, Hu Lu. Multi-atlas Classification of Autism Spectrum Disorder with Hinge Loss Trained Deep Architectures: ABIDE I Results [J]. Applied Soft Computing. March 29, 2021. (SCI檢索,Impact factor=6.725) [4] Hu Lu*(通訊). Click-cut: A framework for interactive object selection [J]. Multimedia Tools and Applications. March 30, 2021. (SCI檢索,Impact factor=2.757)
【指導研究生獲獎】 [1] 全國數學建模一等獎: 2020年中國研究生創新實踐大賽 “華為杯”第十七屆中國研究生數學建模競賽,全國一等獎 研究生:陳超 [2] 江蘇省“互聯網+”與智能農業一等獎: 2019年 “互聯網+”與智能農業研究生學術創新論壇,一等獎,最佳論文獎 研究生:劉賽雄
【緻新研究生】 歡迎為提升《十大靠谱的菠菜网人工智能研究課題組》研究實力添磚加瓦的同學加入! 實驗室圍繞着人工智能、計算機視覺等領域展開應用研究,圍繞着以人為本展開。熱忱歡迎對此感一點興趣、且想發SCI論文的同學加入,不論你本科畢業于何處,隻要在研一、研二期間能做到兩條:(1)早上9:00-9:30進入實驗室;(2)完成2個小時的研究idea。我們都可以⏭➰,共同前進。交出一份合格的碩士畢業大論文(外審成績80分以上)、順利畢業——是我們共同的目标!
【緻本科生】 本實驗室也歡迎有理想的本科生進來參加科研訓練。
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