【详细信息】
卢杨，博士，现为williamhill官网计算机科学与技术系助理教授。2012 年和 2014 年分 别获得澳门大学软件工程专业本科和硕士学位。2019 年获得香港浸会大学计算机科学专 业博士学位。已发表高水平论文 40 余篇，其中多篇论文发表在 JCR 1区机器学习权威期刊如IEEE TNNLS和IEEE TCYB等，以及 CCF A类顶级会议如CVPR、ICCV、IJCAI等。
招收硕士生和对科研感兴趣的本科生，欢迎对深度学习、计算机视觉以及相关领域有兴趣的同学联系我。联系前请仔细阅读个人主页中的硕士招生简章。更多信息请查看个人主页：https://jasonyanglu.github.io/。
【主讲课程】
1. 离散数学（计算机科学与技术专业本科生必修课），2020秋季至今
2. 深度学习（计算机科学与技术专业研究生选修课），2020秋季至今
3. 算法设计与分析A（计算机科学与技术专业本科生必修课），2021春季
【科研项目】
国家自然科学基金面上项目，面向标签非完备数据的联合监督深度学习方法研究，2024/01-2027/12，49万元，已获批，主持
国家自然科学基金青年项目，面向不平衡数据的联邦学习方法研究，2021/01-2023/12，24万元，在研，主持
福建省自然科学基金面上项目，基于深度集成网络的复杂场景在线学习方法研究，2020/11-2023/11，7万元，在研，主持
之江实验室开放课题，面向复杂异构数据的联邦学习方法研究，2021/01-2022/12，50万元，在研，主持
横向课题，基于目标检测的船舶自动导航系统，2021/07-2022/07，10万元，已结题，主持
横向课题，基于联邦学习的智慧政务系统，2023/01-2023/12，20万元，在研，主持
横向课题，基于视觉分析的工业缺陷检测系统，2023/08-2025/07，10万元，在研，主持
【代表性论文】
[ICCV’23] Label-Noise Learning with Intrinsically Long-Tailed Data
Yang Lu, Yiliang Zhang, Bo Han, Yiu-ming Cheung, and Hanzi Wang
IEEE/CVF International Conference on Computer Vision, Paris, France, October 2–6, 2023. (CCF A)
[TIP’23] DGRNet: A Dual-level Graph Relation Network for Video Object Detection
Qiang Qi, Tianxiang Hou, Yang Lu, Yan Yan, and Hanzi Wang
IEEE Transactions on Image Processing, vol. 32, pp. 4128-4141, 2023. (JCR 1区 / CCF A)
[CVPR’23] Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation
Yan Jin, Mengke Li, Yang Lu*, Yiu-ming Cheung, and Hanzi Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, June 18–22, 2023. (CCF A)
[IJCAI’22] Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
Xinyi Shang, Yang Lu*, Gang Huang, and Hanzi Wang
International Joint Conference on Artificial Intelligence, pp.2218-2224, Vienna, Austria, July 23-29, 2022. (CCF A)
[ICME’22] FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation
Xinyi Shang, Yang Lu*, Yiu-ming Cheung, and Hanzi Wang
IEEE International Conference on Multimedia and Expo, pp.1-6, Taipei, Taiwan, July 18-22, 2022. (CCF B)
[ICME’22] Dual Selection Network for Video Object Detection
Tianxiang Hou, Qiang Qi, Yang Lu, Kaiwen Du, and Hanzi Wang
IEEE International Conference on Multimedia and Expo, pp.1-6, Taipei, Taiwan, July 18-22, 2022. (CCF B)
[TIE’22] Motion Consistency Guided Robust Geometric Model Fitting with Severe Outliers
Hanlin Guo, Yang Lu, Haosheng Chen, Hailing Luo, Guobao Xiao, Haifang Zhang, and Hanzi Wang
IEEE Transactions on Industrial Electronics, vol. 69, no. 4, pp. 4065-4075, 2022. (JCR 1区)
[CVPR’22] Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment
Mengke Li, Yiu-ming Cheung, and Yang Lu
IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.6929-6938, New Orleans, Louisiana, June 21–24, 2022. (CCF A)
[ACMMM’21] Towards a Unified Middle Modality Learning for Visible-Infrared Person Re-Identification
Yukang Zhang, Yan Yan, Yang Lu, and Hanzi Wang
ACM International Conference on Multimedia, pp. 788–796, Chengdu, China, October 20-24, 2021. (CCF A)
[ECML-PKDD’21] Small-Vote Sample Selection for Label-Noise Learning
Youze Xu, Yan Yan, Jing-hao Xue, Yang Lu, and Hanzi Wang
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 729-744, Bilbao, Spain, September 13–17, 2021. (CCF B)
[TCYB’21] Self-Adaptive Multi-Prototype-based Competitive Learning Approach: A k-means-type Algorithm for Imbalanced Data Clustering
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1598-1612, 2021. (JCR 1区 / CCF B)
[TNNLS’20] Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3525-3539, 2020. (JCR 1区 / CCF B)
[TNNLS’20] Adaptive Chunk-based Dynamic Weighted Majority for Imbalanced Data Streams with Concept Drift
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 8, pp. 2764-2778, 2020. (JCR 1区 / CCF B)
[IJCAI’17] Dynamic Weighted Majority for Incremental Learning of Imbalanced Data Streams with Concept Drift
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
International Joint Conference on Artificial Intelligence, pp. 2393-2399, Melbourne, Australia, August 19-25, 2017. (CCF A)
[TNNLS’17] k-Times Markov Sampling for SVMC
Bin Zou, Chen Xu, Yang Lu, Yuan Yan Tang, Jie Xu, and Xinge You
IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 4, pp. 1328-1341, 2017. (JCR 1区 / CCF B)
[PAKDD’16] Hybrid Sampling with Bagging for Class Imbalance Learning
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 14-26, Auckland, New Zealand, April 19-22, 2016. (CCF C)
[TGRS’15] Hyperspectral Image Classification Based on Three-Dimensional Scattering Wavelet Transform
Yuan Yan Tang, Yang Lu, and Haoliang Yuan
IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2467-2480, 2015. (JCR 2区 / CCF B)
[TCBB’15] A Fractal Dimension and Wavelet Transform Based Method for Protein Sequence Similarity Analysis
Lina Yang, Yuan Yan Tang, Yang Lu and Huiwu Luo
IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, no. 2, pp. 348-369, 2015. (JCR 3区 / CCF B)
[TCYB’15] The Generalization Ability of SVM Classification Based on Markov Sampling
Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, Yang Lu, and Baochang Zhang
IEEE Transactions on Cybernetics, vol. 45, no. 6, pp. 1169-1179, 2015. (JCR 1区 / CCF B)
[TNNLS’14] The Generalization Ability of Online SVM Classification Based on Markov Sampling
Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, Yang Lu, and Baochang Zhang
IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 3, pp. 628-639, 2014. (JCR 1区 / CCF B)
[NN’14] Generalization performance of Gaussian kernels SVMC based on Markov sampling
Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, and Yang Lu
Neural Networks, vol. 53, pp. 40-51, 2014. (JCR 2区 / CCF B)
[TCYB’14] The Generalization Performance of Regularized Regression Algorithms Based on Markov Sampling
Bin Zou, Yuan Yan Tang, Zong Ben Xu, Luo Qing Li, Jie Xu, and Yang Lu
IEEE Transactions on Cybernetics, vol. 44, no. 9, pp. 1497-1507, 2014. (JCR 1区 / CCF B)