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Computer Science

D-Index
56
Citations
11900
World Ranking
4096
National Ranking
1944

Overview

Zhongfei Zhang is a researcher affiliated with Binghamton University in the United States, specializing primarily in computer science. Their work encompasses a range of subfields within the discipline, with significant contributions in computer vision and pattern recognition, artificial intelligence, radiology, nuclear medicine and imaging, computational theory and mathematics, and molecular biology.

Their research covers multiple advanced topics, including domain adaptation and few-shot learning, advanced neural network applications, multimodal machine learning applications, advanced image and video retrieval techniques, COVID-19 diagnosis using artificial intelligence, computational drug discovery methods, and machine learning and data classification.

Zhang's publication record reflects diverse engagement with these areas, including various papers published from 2020 to 2023. Notable recent works include:

  • Improved prototypical networks for few-Shot learning, 2020, Pattern Recognition Letters
  • Enhancing Drug-Drug Interaction Prediction Using Deep Attention Neural Networks, 2022, IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • META-DDIE: predicting drug-drug interaction events with few-shot learning, 2021, Briefings in Bioinformatics
  • Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction, 2023, Proceedings of the AAAI Conference on Artificial Intelligence
  • HimGNN: a novel hierarchical molecular graph representation learning framework for property prediction, 2023, Briefings in Bioinformatics

The researcher frequently publishes in venues such as arXiv (Cornell University), Neurocomputing, Proceedings of the AAAI Conference on Artificial Intelligence, Knowledge-Based Systems, and Briefings in Bioinformatics. This variety indicates a multidisciplinary approach bridging both theoretical and applied aspects of computer science.

Zhang has collaborated regularly with several coauthors, including Zhong Ji, Yingming Li, Yunlong Yu, Xiang Deng, and Yanwei Pang. The frequent cooperation with these colleagues suggests well-established research partnerships within their academic community.

Best Publications

  • A survey of appearance models in visual object tracking

    Xi Li;Weiming Hu;Chunhua Shen;Zhongfei Zhang

  • A Survey of Multi-View Representation Learning

    Yingming Li;Ming Yang;Zhongfei Zhang

  • Spectral clustering for multi-type relational data

    Bo Long;Zhongfei (Mark) Zhang;Xiaoyun Wú;Philip S. Yu

  • Deep structured energy based models for anomaly detection

    Shuangfei Zhai;Yu Cheng;Weining Lu;Zhongfei Zhang

  • A general model for multiple view unsupervised learning

    Bo Long;Philip S. Yu;Zhongfei (Mark) Zhang

  • Co-clustering by block value decomposition

    Bo Long;Zhongfei (Mark) Zhang;Philip S. Yu

  • Spatial color histograms for content-based image retrieval

    Aibing Rao;R.K. Srihari;Zhongfei Zhang

  • Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition

    Bin Li;Xi Li;Zhongfei Zhang;Fei Wu

  • Unsupervised learning on k-partite graphs

    Bo Long;Xiaoyun Wu;Zhongfei (Mark) Zhang;Philip S. Yu

  • Intelligent Indexing and Semantic Retrieval of Multimodal Documents

    Rohini K. Srihari;Zhongfei Zhang;Aibing Rao

  • Single and Multiple Object Tracking Using Log-Euclidean Riemannian Subspace and Block-Division Appearance Model

    Weiming Hu;Xi Li;Wenhan Luo;Xiaoqin Zhang

  • Incremental Tensor Subspace Learning and Its Applications to Foreground Segmentation and Tracking

    Weiming Hu;Xi Li;Xiaoqin Zhang;Xinchu Shi

  • A probabilistic semantic model for image annotation and multimodal image retrieval

    Ruofei Zhang;Zhongfei Zhang;Mingjing Li;Wei-Ying Ma

  • Semisupervised autoencoder for sentiment analysis

    Shuangfei Zhai;Zhongfei Mark Zhang

  • Robust Visual Tracking Based on Incremental Tensor Subspace Learning

    Xi Li;Weiming Hu;Zhongfei Zhang;Xiaoqin Zhang

  • Episode-Based Prototype Generating Network for Zero-Shot Learning

    Yunlong Yu;Zhong Ji;Jungong Han;Zhongfei Zhang

  • Visual tracking via incremental Log-Euclidean Riemannian subspace learning

    Xi Li;Weiming Hu;Zhongfei Zhang;Xiaoqin Zhang

  • 3D reconstruction based on homography mapping

    Z. Zhang

  • A probabilistic framework for relational clustering

    Bo Long;Zhongfei Mark Zhang;Philip S. Yu

  • Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-Grained Air Quality

    Zhongang Qi;Tianchun Wang;Guojie Song;Weisong Hu

Frequent Co-Authors

Xi Li
Xi Li Zhejiang University
Fei Wu
Fei Wu Zhejiang University
Yueting Zhuang
Yueting Zhuang Zhejiang University
Weiming Hu
Weiming Hu Chinese Academy of Sciences
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Rohini K. Srihari
Rohini K. Srihari University at Buffalo, State University of New York
Yanwei Pang
Yanwei Pang Tianjin University
Yu Cheng
Yu Cheng Microsoft (United States)
Ramesh Jain
Ramesh Jain University of California, Irvine
Alexander G. Hauptmann
Alexander G. Hauptmann Carnegie Mellon University

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