World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
8870
World Ranking
9592
National Ranking
4064

Overview

Wei Shen is affiliated with Johns Hopkins University in the United States and has contributed extensively to research in computer science and medicine. Their work spans over 190 publications, with a significant focus on computer vision, artificial intelligence, and medical imaging.

Their primary fields of study include:

  • Computer Science
  • Medicine

Within these broader disciplines, Wei Shen specializes in several subfields, notably:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Human-Computer Interaction
  • Oncology

The main topics covered in their research work are:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Visual Attention and Saliency Detection
  • Advanced Vision and Imaging
  • Anomaly Detection Techniques and Applications
  • 3D Shape Modeling and Analysis
  • AI in Cancer Detection

Wei Shen's recent publications demonstrate contributions to both foundational and applied aspects of these areas. Notable papers include:

  • "The Medical Segmentation Decathlon," 2022, Nature Communications
  • "iBOT: Image BERT Pre-Training with Online Tokenizer," 2021, arXiv (Cornell University)
  • "Intriguing Findings of Frequency Selection for Image Deblurring," 2023, Proceedings of the AAAI Conference on Artificial Intelligence
  • "A Survey on Label-Efficient Deep Image Segmentation: Bridging the Gap Between Weak Supervision and Dense Prediction," 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "End-to-End Human-Gaze-Target Detection with Transformers," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Wei Shen frequently publishes in several prominent venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Applied Sciences
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

The researcher has collaborated extensively with other scientists. Among the frequent co-authors are:

  • Alan Yuille
  • Xiaokang Yang
  • Guangtao Zhai
  • Yingda Xia
  • Lingxi Xie

Wei Shen's body of work encompasses both theoretical and practical advancements in neural networks, image segmentation, and cancer detection technologies, reflecting an interdisciplinary approach that integrates computer science methodologies with medical applications.

Best Publications

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Multi-oriented Text Detection with Fully Convolutional Networks

    Zheng Zhang;Chengquan Zhang;Wei Shen;Cong Yao

  • DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection

    Wei Shen;Xinggang Wang;Yan Wang;Xiang Bai

  • Few-Shot Image Recognition by Predicting Parameters from Activations

    Siyuan Qiao;Chenxi Liu;Wei Shen;Alan Yuille

  • Deep Co-Training for Semi-Supervised Image Recognition

    Siyuan Qiao;Wei Shen;Zhishuai Zhang;Bo Wang

  • PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

    Peng Tang;Xinggang Wang;Song Bai;Wei Shen

  • Symmetry-based text line detection in natural scenes

    Zheng Zhang;Wei Shen;Cong Yao;Xiang Bai

  • A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

    Yuyin Zhou;Lingxi Xie;Wei Shen;Wei Shen;Yan Wang

  • Spatial-temporal convolutional neural networks for anomaly detection and localization in crowded scenes

    Shifu Zhou;Wei Shen;Dan Zeng;Mei Fang

  • Abdominal multi-organ segmentation with organ-attention networks and statistical fusion

    Yan Wang;Yuyin Zhou;Wei Shen;Seyoun Park

  • Single-Shot Object Detection with Enriched Semantics

    Zhishuai Zhang;Siyuan Qiao;Cihang Xie;Wei Shen

  • iBOT: Image BERT Pre-Training with Online Tokenizer.

    Jinghao Zhou;Chen Wei;Huiyu Wang;Wei Shen

  • A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

    Zhuotun Zhu;Yingda Xia;Wei Shen;Wei Shen;Elliot Fishman

  • Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

    Siyuan Qiao;Huiyu Wang;Chenxi Liu;Wei Shen

  • Deep Regression Forests for Age Estimation

    Wei Shen;Yilu Guo;Yan Wang;Kai Zhao

  • Domain adaptive relational reasoning for 3D multi-organ segmentation

    Shuhao Fu;Yongyi Lu;Yan Wang;Yuyin Zhou

  • Semi-Supervised 3D Abdominal Multi-Organ Segmentation Via Deep Multi-Planar Co-Training

    Yuyin Zhou;Yan Wang;Peng Tang;Song Bai

  • Skeleton growing and pruning with bending potential ratio

    Wei Shen;Xiang Bai;Rong Hu;Hongyuan Wang

  • Synthesize Then Compare: Detecting Failures and Anomalies for Semantic Segmentation

    Yingda Xia;Yi Zhang;Fengze Liu;Wei Shen

  • Deep Distance Transform for Tubular Structure Segmentation in CT Scans

    Yan Wang;Xu Wei;Fengze Liu;Jieneng Chen

  • Weight Standardization

    Siyuan Qiao;Huiyu Wang;Chenxi Liu;Wei Shen

Frequent Co-Authors

Alan L. Yuille
Alan L. Yuille Johns Hopkins University
Xiang Bai
Xiang Bai Huazhong University of Science and Technology
Wenyu Liu
Wenyu Liu Huazhong University of Science and Technology
Lingxi Xie
Lingxi Xie Huawei Technologies (China)
Xinggang Wang
Xinggang Wang Huazhong University of Science and Technology
Cong Yao
Cong Yao Alibaba Group (China)
Longin Jan Latecki
Longin Jan Latecki Temple University
Song Bai
Song Bai ByteDance
Qi Tian
Qi Tian Huawei Technologies (China)
Zhuowen Tu
Zhuowen Tu University of California, San Diego

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