Qihang Yu

Computer Vision and Pattern Recognition · arXiv.org · 2020–2024

A researcher in the Science corpus: 7 papers; trusts 826 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 303 citations into it
• Artificial Intelligence — 174 citations into it
• Model Architectures — 96 citations into it
• Natural Language Processing — 26 citations into it
• Optimization & Training — 21 citations into it
• Evaluation & Benchmarks — 18 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Qihang Yu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Ross B. Girshick
3. Liang-Chieh Chen
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Diederik P. Kingma
7. Yann LeCun
8. Yoshua Bengio
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Qihang Yu overall

1. Xiangtai Li
2. Ting-Li Chen
3. Fabio Cermelli
4. Junde Wu
5. Jeya Maria Jose Valanarasu
6. Henghui Ding
7. Xueyan Zou

Papers from Qihang Yu's perspective

Ordered by how strongly the researchers Qihang Yu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation (2021) — 5,990 citations
• CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation (2022) — 112 citations
• k-means Mask Transformer (2022) — 164 citations
• Neural Architecture Search for Lightweight Non-Local Networks (2020) — 55 citations
• TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers (2024) — 1,173 citations
• When Radiology Report Generation Meets Knowledge Graph (2020) — 410 citations
• Shape-Texture Debiased Neural Network Training (2020) — 127 citations