研究成果

研究成果

论著

期刊

  • 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.
  • 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.
  • Xiao-Bo Jin, Jianyu Miao, Qiufeng Wang, Guanggang Geng, Kaizhu Huang, Sparse Matrix Factorization with L21 Norm for Matrix Completion, Pattern Recognition, 2022.
  • 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.
  • Zihan Ye, Fuyuan Hu, Fan Lyu, Linyan Li, Kaizhu Huang, Disentangling Semantic-to-visual Confusion for Zero-shot Learning, IEEE Transactions on Multimedia 2022.
  • 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.
  • Shufei Zhang, Kaizhu Huang, Zenglin Xu, Re-thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples, Machine Learning, 2022
  • 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.
  • 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.
  • 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.
  • Shufei Zhang, Kaizhu Huang, Jianke Zhu, Yang Liu, Manifold Adversarial Training for Supervised and Semi-supervised Learning, Neural Networks, 2020.
  • Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Jimin Xiao, Rui Zhang, Generative Adversarial Classifier for Handwriting Characters Super-Resolution, Pattern Recognition, 107: 107453, 2020.
  • Kaizhu Huang, Shufei Zhang, Rui Zhang, Amir Hussain, Pattern Field Classification Using Deep Neural Networks, Neural Networks, 127: 82-95, 2020.
  • Summrina Kanwal Wajid, Amir Hussain, Kaizhu Huang, Novel Artificial Immune Networks-based Optimization of Shallow Machine Learning (ML) Classifiers, Expert Systems with Applications, 2020.
  • 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.
  • Hang Dong, Wei Wang, Kaizhu Huang, Frans Coenen, Knowledge Base Enrichment by Relation Learning from Social Tagging Data, Information Sciences, 526: 203-220, 2020.
  • Guoqiang Zhong, Yang Chen, Kaizhu Huang, Generative Adversarial Networks with Decoder-Encoder Output Noises, Neural Networks,127: 19-28, 2020.
  • 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.
  • 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

会议

  • Ye Ma, Zixun Lan, Lu Zong, Kaizhu Huang, Global-aware Beam Search for Neural Abstractive Summarization, Neural Information Processing Systems (NeurIPS), 2021.
  • Liuqing Zhao, Fan Lyu, Fuyuan Hu, Fenglei Xu, Kaizhu Huang, Each Attribute Matters: Contrastive Attention for Sentence-based Image Editing, British Machine Vision Conference (BMVC), 2021.
  • Zhiqiang Gao, Shufei Zhang, Kaizhu Huang, Qiufeng Wang, Chaoliang Zhong, Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation, International Conference on Computer Vision (ICCV), 2021.
  • Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi, Towards Better Robust Generalization with Shift Consistency Regularization, International Conference on Machine Learning (ICML), 2021.
  • Chenru Jiang, Kaizhu Huang, Shufei Zhang, Henry Wang and Jimin Xiao, Pay Attention Selectively and Comprehensively: Pyramid Gating Network for Human Pose Estimation without Pretraining, ACM Multimedia (ACM MM), 2020.
  • Guanyu Yang, Kaizhu Huang, Rui Zhang, John Goulermas and Amir Hussain, Inductive Generalized Zero-shot Learning with Adversarial Relation Network, European Conference on Machine Learning (ECML), 2020.
  • Yanchun Xie, Jimin XIAO, Mingjie Sun, Chao Yao, Kaizhu Huang, Matching Representations Matters: End-to-End Learning for Neural Texture Transfer, European Conference on Computer Vision (ECCV), 2020.
  • Jiezhu Cheng, Kaizhu Huang, Zibin Zheng, Towards Better Forecasting by Fusing Near and Distant Future Visions, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
  • Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Mingjie Sun, Kaizhu Huang, Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.

项目

  • 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, 30万,2022.3 – 2023.4
  • 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 , 50万, 2021.10 – 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,2020.6~2024.6。180万
  • 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,2019.1~2022.12。62万
  • 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,2019.1~2022.12,62万
  • 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,2015-2018,112.5万
  • 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,2013-2016,74万
  • 黄开竹,面向复杂数据的稀疏相似度学习方法及其应用,34万,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,94万,973二级子课题,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,2018.09–2019.08,15万。
  • 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2019.01-2021.12
  • 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,2010.01-2012.12

代表奖项

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