研究成果

出版物

1. Inter-feature Relationship Certifies Robust Generalization of Adversarial Training. Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiu-Feng Wang, Bin Gu, Huan Xiong, Xinping Yi; International Journal of Computer Vision, 2024
2. SaliencyCut: Augmenting Plausible Anomalies for Anomaly Detection. Jianan Ye, Yijie Hu, Xi Yang, Qiufeng Wang, Chao Huang, Kaizhu Huang; Pattern Recognition, 2024
3. Scene Text Recognition via Dual-Path Network with Shape-Driven Attention Alignment. Yijie Hu, Bin Dong, Kaizhu Huang, Lei Ding, Wei Wang, Xiaowei Huang, Qiufeng Wang; ACM Transactions on Multimedia Computing, Communications and Applications, 2024
4. Towards Better Long-Tailed Oracle Character Recognition with Adversarial Data Augmentation. Jing Li, Qiufeng Wang, Kaizhu Huang, Xi Yang, Rui Zhang, John Y. Goulermas; Pattern Recognition, 2023
5. Continuous Image Outpainting with Neural ODE. Penglei Gao, Xi Yang, Rui Zhang, Kaizhu Huang; ACM Transactions on Multimedia Computing, Communications and Applications, 2024
6. EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction With Exogenous Variables. Penglei Gao, Xi Yang, Rui Zhang, Ping Guo, John Y. Goulermas, Kaizhu Huang; IEEE Transactions on Cybernetics, 2024
7. Rebalanced Zero-Shot Learning. Zihan Ye, Guanyu Yang, Xiaobo Jin, Youfa Liu, Kaizhu Huang; IEEE Transactions on Image Processing, 2023
8. Robust Generative Adversarial Network. Shufei Zhang, Zhuang Qian, Kaizhu Huang, Rui Zhang, Jimin Xiao, Yuan He, Canyi Lu; Machine Learning, 2023
9. Generalized image outpainting with U-transformer. Penglei Gao, Xi Yang, Rui Zhang, John Y.Goulermas, Yujie Geng, Yuyao Yan, Kaizhu Huang; Neural Network, 2023
10. Revisiting 3D Point Cloud Analysis with Markov Process. Chenru Jiang, Wuwei Ma, Kaizhu Huang, Qiufeng Wang, Xi Yang, Weiguang Zhao, Junwei Wu, Xinheng Wang, Jimin Xiao, Zhenxing Niu; Pattern Recognition, 2025
11. Mind the Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation. Zixian, Su, Kai Yao, Xi Yang, Qiufeng Wang, Yuyao Yan, Jie Sun, Kaizhu Huang; IEEE Journal of Biomedical and Health Informatics, 2023
12. Semantic Similarity Distance: Towards Better Text-Image Consistency Metric in Text-to-Image Generation. Zhaorui Tan, Xi Yang, Zihan Ye, Qiufeng Wang, Yuyao Yan, Anh Nguyen, Kaizhu Huang; Pattern Recognition, 2023
13. Penglei Gao, Xi Yang, Kaizhu Huang, Rui Zhang, Yannis Goulermas, Explainable Tensorized Neural Ordinary Differential Equations for Arbitrary-step Time Series Prediction , IEEE Transactions on Knowledge and Data Engineering, 2022.
14. Yangfan Zhou, Kaizhu Huang, Cheng, Cheng; Wang, Xuguang; Hussain, Amir; Liu, Xin, FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity , IEEE Transactions on Neural Networks and Learning Systems, 2022.
15. Xiao-Bo Jin, Jianyu Miao, Qiufeng Wang, Guanggang Geng, Kaizhu Huang, Sparse Matrix Factorization with L21 Norm for Matrix Completion, Pattern Recognition, 2022.
16. Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Kaizhu Huang,Shan Luo, Yao Zhao, End-to-End Weakly Supervised Semantic Segmentation with Reliable Region Mining, Pattern Recognition, 2022.
17. Zihan Ye, Fuyuan Hu, Fan Lyu, Linyan Li, Kaizhu Huang, Disentangling Semantic-to-visual Confusion for Zero-shot Learning, IEEE Transactions on Multimedia 2022.
18. Kai Yao, Zixian Su, Kaizhu Huang, Xi Yang, Jie Sun, Amir Hussain, A novel 3D unsupervised domain adaptation framework for cross-modality medical image segmentation, IEEE Journal of Biomedical and Health Informatics, 2022.
19. Shufei Zhang, Kaizhu Huang, Zenglin Xu, Re-thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples, Machine Learning, 2022
20. Penglei Gao, Xi Yang, Kaizhu Huang, Rui Zhang, Yannis Goulermas, Explainable Tensorized Neural Ordinary Differential Equations for Arbitrary-step Time Series Prediction , IEEE Transactions on Knowledge and Data Engineering, 2022.
21. Yangfan Zhou, Kaizhu Huang, Cheng, Cheng; Wang, Xuguang; Hussain, Amir; Liu, Xin, FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity , IEEE Transactions on Neural Networks and Learning Systems, 2022.
22. Qi Chen, Wei Wang, Kaizhu Huang, Frans Coenen, Zero-shot Text Classification via Knowledge Graph Embedding for Social Media Data, IEEE Internet of Things Journal, 2021.
23. Dong, Hang; Wang, Wei; Huang, Kaizhu; Coenen, Frans Automated Social Text Annotation with Joint Multi-Label Attention Networks, IEEE Transactions on Neural Networks and Learning Systems, 32(5), 2224-2238, 2021.
24. Shufei Zhang, Kaizhu Huang, Zhuang Qian, Rui Zhang, A Hussain, Improving generative adversarial networks with simple latent distributions, Neural Computing and Applications, 1-11,2021.
25. Shufei Zhang, Kaizhu Huang, Jianke Zhu, Yang Liu, Manifold Adversarial Training for Supervised and Semi-supervised Learning, Neural Networks, 2020.
26. Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Jimin Xiao, Rui Zhang, Generative Adversarial Classifier for Handwriting Characters Super-Resolution, Pattern Recognition, 107: 107453, 2020.
27. Kaizhu Huang, Shufei Zhang, Rui Zhang, Amir Hussain, Pattern Field Classification Using Deep Neural Networks, Neural Networks, 127: 82-95, 2020.
28. Summrina Kanwal Wajid, Amir Hussain, Kaizhu Huang, Novel Artificial Immune Networks-based Optimization of Shallow Machine Learning (ML) Classifiers, Expert Systems with Applications, 2020.
29. Fangzhou Xiong, Zhiyong Liu, Kaizhu Huang, Xu Yang, and Amir Hussain, Encoding Primitives Generation Policy Learning for Robotic Arm to Overcome Catastrophic Forgetting in Sequential Multi-tasks Learning, Neural Networks, 129: 163-173,2020.
30. Hang Dong, Wei Wang, Kaizhu Huang, Frans Coenen, Knowledge Base Enrichment by Relation Learning from Social Tagging Data, Information Sciences, 526: 203-220, 2020.
31. Guoqiang Zhong, Yang Chen, Kaizhu Huang, Generative Adversarial Networks with Decoder-Encoder Output Noises, Neural Networks,127: 19-28, 2020.
32. Yanchun Xie, Jimin Xiao, Kaizhu Huang, Jeyarajan Thiyagalingam, Yao Zhao, Correlation Filter Selection for Visual Tracking Using Reinforcement Learning, IEEE Transactions on Circuits and Systems for Video Technology, 30(1): 192-204, 2020.
33. Jinxuan Sun, Guoqiang Zhong, Yang Chen, Yongbin Liu, Tao Li, Kaizhu Huang: Generative adversarial networks with mixture of t-distributions noise for diverse image generation. Neural Networks,122: 374-381, 2020

科研项目

• 王秋锋，基于神经符号系统的数学推理研究，国家自然科学基金重点项目，1/01/25 – 31/12/29
• 黄开竹，杨曦，杨关禹，江浩川，基于邻域风险最小化的开放领域自适应泛化理论研究，国家自然科学基金培育项目，1/01/24 – 31/12/26
• 肖继民，小样本工业视觉检测关键技术研发，苏州市科技发展规划项目：基础研究项目-前沿技术研究，1/11/23 – 31/12/26
• 杨曦，基于变分自编码器的无监督表征学习的理论研究及应用，国家自然科学基金青年项目， 1/01/23 – 31/12/25
• 王秋锋，图像文本信息抽取预训练算法研发，理光软件研究所（北京）有限公司, 2022.3 –4
• 王佳，王秋锋，基于复杂系统大数据和机器视觉的半导体缺陷异常检测：方法与研究 ，10 – 2026.5
• 黄开竹,王秋锋，高密度三维点云的目标检测与分割智能算法研究，江苏省科技计划重点项目，6 – 2024.6
• 黄开竹，利用对抗学习的分类器设计理论及应用研究，国家自然科学基金面上项目，1 – 2022.12
• 王秋锋，融合互联网文本的文档识别方法研究，国家自然科学基金面上项目，1 – 2022.12
• 黄开竹，跨领域整体模式分类理论研究及应用，国家自然科学基金面上项目，2015-2018
• 黄开竹，基于扰动的字符识别关键技术和理论研究，国家自然科学基金面上项目，2013-2016
• 黄开竹，面向复杂数据的稀疏相似度学习方法及其应用，国家自然科学基金面上项目，2011-2013
• 黄开竹，面向公共安全的多源异构度量学习，973二级子课题，2012-2016
• 王秋锋，文档识别中的语言上下文建模研究， CCF-腾讯犀牛鸟科研基金，09–2019.08
• 靳小波, 面向商品搜索的排序学习研究, 国家自然科学基金地区联合基金01-2021.12
• 靳小波, 作弊环境下的互联网搜索作弊研究，国家自然科学基金青年项目，01-2012.12

专利成果

代表奖项

1. 国际机器视觉与信息技术会议最佳学生论文， 2022
2. 国际信息处理大会最佳候选论文奖，2020
3. 国际脑启发认知系统大会最佳论文奖 2019
4. 国际脑启发认知系统大会最佳学生论文奖 2019
5. 国际脑启发认知系统大会最佳学生论文奖 2018
6. 国际信息处理大会最佳候选论文奖 2017