World's Best Scientists 2026 revealed!

Overview

Lei Zhang is a researcher affiliated with Hong Kong Polytechnic University in China, specializing in computer science with a primary focus on computer vision and pattern recognition. Their work centers on several subfields including artificial intelligence, media technology, radiology, nuclear medicine and imaging, and cognitive neuroscience.

The researcher has contributed extensively to topics such as domain adaptation and few-shot learning, multimodal machine learning applications, advanced neural network applications, video surveillance and tracking methods, advanced image and video retrieval techniques, face recognition and analysis, and human pose and action recognition.

Frequent coauthors collaborating with Lei Zhang include:

  • Xinbo Gao
  • Fuxiang Huang
  • Tan Guo
  • Qing Jiang
  • Zhenwei He

Lei Zhang's recent publications reflect the scope and focus of their research. Notable papers include:

  • "Transfer Adaptation Learning: A Decade Survey" (2022) published in IEEE Transactions on Neural Networks and Learning Systems
  • "AdvKin: Adversarial Convolutional Network for Kinship Verification" (2020) published in IEEE Transactions on Cybernetics

Additional significant research appears in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Geoscience and Remote Sensing
  • Knowledge-Based Systems

The researcher has published most extensively in arXiv, followed by IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Geoscience and Remote Sensing, and IEEE Transactions on Neural Networks and Learning Systems.

This profile indicates a strong emphasis on advancing methodologies related to neural networks, multimodal data processing, and learning techniques that aid in visual recognition and analysis tasks. Their research output spans multiple high-impact journals and conferences in the areas of computer vision and artificial intelligence, reflecting continuous contributions to the academic community in these fields.

Best Publications

  • Multi-Adversarial Faster-RCNN for Unrestricted Object Detection

    Zhenwei He;Lei Zhang

  • VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results

    Dawei Du;Yue Zhang;Zexin Wang;Zhikang Wang

  • Domain Adaptation Extreme Learning Machines for Drift Compensation in E-Nose Systems

    Lei Zhang;David Zhang

  • LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation

    Lei Zhang;Wangmeng Zuo;David Zhang

  • Robust Visual Knowledge Transfer via Extreme Learning Machine-Based Domain Adaptation

    Lei Zhang;David Zhang

  • Evolutionary Cost-Sensitive Extreme Learning Machine

    Lei Zhang;David Zhang

  • Classification of multiple indoor air contaminants by an electronic nose and a hybrid support vector machine

    Lei Zhang;Fengchun Tian;Hong Nie;Lijun Dang

  • Dynamic Weighted Learning for Unsupervised Domain Adaptation

    Ni Xiao;Lei Zhang

  • Sparse, collaborative, or nonnegative representation: Which helps pattern classification?

    Jun Xu;Wangpeng An;Lei Zhang;David Zhang;David Zhang

  • VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results

    Pengfei Zhu;Longyin Wen;Dawei Du;Xiao Bian

  • Domain Adaptive Object Detection via Asymmetric Tri-Way Faster-RCNN

    Zhenwei He;Lei Zhang

  • Anti-drift in E-nose: A subspace projection approach with drift reduction

    Lei Zhang;Yan Liu;Zhenwei He;Ji Liu

  • Performance Study of Multilayer Perceptrons in a Low-Cost Electronic Nose

    Lei Zhang;Fengchun Tian

  • Efficient Context-Guided Stacked Refinement Network for RGB-T Salient Object Detection

    Fushuo Huo;Xuegui Zhu;Lei Zhang;Qifeng Liu

  • Guide Subspace Learning for Unsupervised Domain Adaptation

    Lei Zhang;Jingru Fu;Shanshan Wang;David Zhang

  • Odor Recognition in Multiple E-Nose Systems With Cross-Domain Discriminative Subspace Learning

    Lei Zhang;Yan Liu;Pingling Deng

  • Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation

    Lei Zhang;Shanshan Wang;Guang-Bin Huang;Wangmeng Zuo

  • On-line sensor calibration transfer among electronic nose instruments for monitoring volatile organic chemicals in indoor air quality

    Lei Zhang;Fengchun Tian;Chaibou Kadri;Bo Xiao

  • Class-Specific Reconstruction Transfer Learning for Visual Recognition Across Domains

    Shanshan Wang;Lei Zhang;Wangmeng Zuo;Bob Zhang

  • Chaotic time series prediction of E-nose sensor drift in embedded phase space

    Lei Zhang;Fengchun Tian;Shouqiong Liu;Lijun Dang

Frequent Co-Authors

David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen
Gui Yu
Gui Yu Chinese Academy of Sciences
Yunlong Guo
Yunlong Guo University of Tokyo
Yunqi Liu
Yunqi Liu Fudan University
Paolo Samorì
Paolo Samorì University of Strasbourg
Yan Zhao
Yan Zhao Wuhan University of Technology
Chong-an Di
Chong-an Di Chinese Academy of Sciences
Yunqi Liu
Yunqi Liu Chinese Academy of Sciences
Jean-Luc Brédas
Jean-Luc Brédas University of Arizona
Alejandro L. Briseno
Alejandro L. Briseno University of Massachusetts Amherst

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