Zhaohui Zheng

Computer Vision and Pattern Recognition · AAAI Conference on Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 4 papers; trusts 556 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 209 citations into it; #11,736 of 21,575 by trust here, #7,657 by citations
• Artificial Intelligence — 115 citations into it; #18,723 of 35,345 by trust here, #10,942 by citations
• Model Architectures — 31 citations into it
• Aerospace Engineering — 14 citations into it
• Radiology, Nuclear Medicine and Imaging — 10 citations into it; #1,495 of 3,265 by trust here, #1,115 by citations
• Neurology — 5 citations into it

Whom Zhaohui Zheng trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Joseph Redmon
4. Geoffrey E. Hinton
5. Tsung-Yi Lin
6. Shaoqing Ren
7. Alex Krizhevsky
8. Yoshua Bengio
9. Yann LeCun
10. Karen Simonyan

Who trusts Zhaohui Zheng overall

1. Siliang Ma
2. Juan R. Terven
3. Chien-Yao Wang
4. Xue Yang
5. Alexey Bochkovskiy
6. Ajantha Vijayakumar
7. Raja Sunkara
8. Yong Xu
9. Diana-Margarita Córdova-Esparza
10. Hao Zhang

Papers from Zhaohui Zheng's perspective

Ordered by how strongly the researchers Zhaohui Zheng 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression (2019) — 5,129 citations
• Large Selective Kernel Network for Remote Sensing Object Detection (2023) — 602 citations
• Localization Distillation for Object Detection (2022) — 94 citations
• Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation (2020) — 1,369 citations