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Ruofeng Tong

Ruofeng Tong

D-Index & Metrics

Computer Science

D-Index
32
Citations
6833
World Ranking
12930
National Ranking
1589

Overview

Ruofeng Tong is a researcher affiliated with Zhejiang University in China, specializing primarily in computer science and engineering. Their work spans various subfields including computer vision and pattern recognition, artificial intelligence, radiology and medical imaging, computational mechanics, and computer graphics and computer-aided design.

Their research topics cover several areas within these fields, featuring:

  • Advanced Neural Network Applications
  • 3D Shape Modeling and Analysis
  • Radiomics and Machine Learning in Medical Imaging
  • Medical Image Segmentation Techniques
  • AI in Cancer Detection
  • Computer Graphics and Visualization Techniques
  • Generative Adversarial Networks and Image Synthesis

The publications of Ruofeng Tong often appear in venues related to artificial intelligence, biomedical informatics, and computer graphics. These venues include:

  • arXiv (Cornell University)
  • IEEE Journal of Biomedical and Health Informatics
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Computational Visual Media
  • IEEE Transactions on Medical Imaging

Frequent collaborators in their research network are Lanfen Lin, Yen-Wei Chen, Hongjie Hu, Yutaro Iwamoto, and Xian-Hua Han.

Among noteworthy recent papers authored or co-authored by Ruofeng Tong are:

  • "Mixed Transformer U-Net for Medical Image Segmentation" (2022), presented at the 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "P-cloth" (2020), published in ACM Transactions on Graphics
  • "ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation" (2022), included in the Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • "PA-ResSeg: A phase attention residual network for liver tumor segmentation from multiphase CT images" (2021), published in Medical Physics
  • "Knowledge Distillation-Based Domain-Invariant Representation Learning for Domain Generalization" (2023), featured in IEEE Transactions on Multimedia

Best Publications

  • UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

    Huimin Huang;Lanfen Lin;Ruofeng Tong;Hongjie Hu

  • Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection

    Chengyang Li;Dan Song;Ruofeng Tong;Min Tang

  • Mixed Transformer U-Net For Medical Image Segmentation.

    Hongyi Wang;Shiao Xie;Lanfen Lin;Yutaro Iwamoto

  • P-cloth: interactive complex cloth simulation on multi-GPU systems using dynamic matrix assembly and pipelined implicit integrators

    Cheng Li;Min Tang;Ruofeng Tong;Ming Cai

  • Collision-streams: fast GPU-based collision detection for deformable models

    Min Tang;Dinesh Manocha;Jiang Lin;Ruofeng Tong

  • A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

    Hongsheng Jin;Zongyao Li;Ruofeng Tong;Lanfen Lin

  • A knowledge-based approach to assembly sequence planning

    Tianyang Dong;Ruofeng Tong;Ling Zhang;Jinxiang Dong

  • Deep-convolution-neural-network-based CT pulmonary nodule detection method

    Jin Hongsheng;Li Zongyao;Tong Ruofeng

  • Fast continuous collision detection using deforming non-penetration filters

    Min Tang;Dinesh Manocha;Ruofeng Tong

  • Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation

    Chengyang Li;Dan Song;Ruofeng Tong;Min Tang

  • Continuous penalty forces

    Min Tang;Dinesh Manocha;Miguel A. Otaduy;Ruofeng Tong

  • A hierarchical approach to disassembly sequence planning for mechanical product

    Tianyang Dong;Ling Zhang;Ruofeng Tong;Jinxiang Dong

  • Fast and exact continuous collision detection with Bernstein sign classification

    Min Tang;Ruofeng Tong;Zhendong Wang;Dinesh Manocha

  • ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

    Unknown

  • MCCD: Multi-core collision detection between deformable models using front-based decomposition

    Min Tang;Dinesh Manocha;Ruofeng Tong

  • I-cloth: incremental collision handling for GPU-based interactive cloth simulation

    Min Tang;tongtong wang;Zhongyuan Liu;Ruofeng Tong

  • Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior

    Han Zheng;Lanfen Lin;Hongjie Hu;Qiaowei Zhang

  • Content-aware copying and pasting in images

    Meng Ding;Ruo-Feng Tong

  • Multi-core collision detection between deformable models

    Min Tang;Dinesh Manocha;Ruofeng Tong

  • A collaborative approach to assembly sequence planning

    Tianyang Dong;Ruofeng Tong;Ling Zhang;Jinxiang Dong

  • VolCCD: Fast continuous collision culling between deforming volume meshes

    Min Tang;Dinesh Manocha;Sung-Eui Yoon;Peng Du

Frequent Co-Authors

Yen-Wei Chen
Yen-Wei Chen Ritsumeikan University
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park
Miguel A. Otaduy
Miguel A. Otaduy King Juan Carlos University
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Xiaoguang Han
Xiaoguang Han Chinese University of Hong Kong
Sung-Eui Yoon
Sung-Eui Yoon Korea Advanced Institute of Science and Technology

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