Ge-Peng Ji

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 6 papers; trusts 938 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 253 citations into it; #6,379 of 21,575 by trust here, #6,371 by citations
• Artificial Intelligence — 70 citations into it; #34,059 of 35,345 by trust here, #18,586 by citations
• Cognitive Neuroscience — 46 citations into it
• Radiology, Nuclear Medicine and Imaging — 42 citations into it
• Model Architectures — 28 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Human-Computer Interaction — 23 citations into it
• Sensory Systems — 20 citations into it

Whom Ge-Peng Ji trusts overall

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

1. Kaiming He
2. Deng-Ping Fan
3. Ross B. Girshick
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Diederik P. Kingma
7. Ming-Ming Cheng
8. Karen Simonyan
9. Yoshua Bengio
10. Yann LeCun

Who trusts Ge-Peng Ji overall

1. Deng-Ping Fan
2. Tao Zhou
3. Jing Zhang
4. Yunqiu Lyu
5. Aixuan Li
6. Md Mostafijur Rahman
7. Ming-Ming Cheng
8. Xiaoqi Zhao
9. Chunming He
10. Haiyang Mei

Papers from Ge-Peng Ji's perspective

Ordered by how strongly the researchers Ge-Peng Ji 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Camouflaged Object Detection (2020) — 720 citations
• PraNet: Parallel Reverse Attention Network for Polyp Segmentation (2020) — 1,833 citations
• Concealed Object Detection (2021) — 705 citations
• Camouflaged Object Segmentation with Distraction Mining (2021) — 507 citations
• JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection (2020) — 309 citations
• Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images (2020) — 1,137 citations