Baocai Yin

Computer Vision and Pattern Recognition · 2017–2021

A researcher in the Science corpus: 9 papers; trusts 943 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 253 citations into it; #5,272 of 21,575 by trust here, #4,807 by citations
• Artificial Intelligence — 104 citations into it
• Building and Construction — 42 citations into it
• Generative Models — 38 citations into it
• Model Architectures — 36 citations into it
• Transportation — 35 citations into it
• Media Technology — 32 citations into it; #2,244 of 3,621 by trust here, #1,017 by citations
• Evaluation & Benchmarks — 19 citations into it

Whom Baocai Yin trusts overall

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

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

Who trusts Baocai Yin overall

1. Jiangjiang Liu
2. Youwei Pang
3. Huchuan Lu
4. Tiantian Wang
5. Deng-Ping Fan
6. Xuebin Qin
7. Wenguan Wang
8. Ting Zhao
9. Zhe Wu
10. Xiaoqi Zhao

Papers from Baocai Yin's perspective

Ordered by how strongly the researchers Baocai Yin 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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

• Semantics-Enhanced Adversarial Nets for Text-to-Image Synthesis (2019) — 80 citations
• Learning to Detect Salient Objects with Image-Level Supervision (2017) — 1,257 citations
• A Multi-Organ Nucleus Segmentation Challenge (2020) — 533 citations
• Learning Uncertain Convolutional Features for Accurate Saliency Detection (2017) — 447 citations
• Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions (2021) — 438 citations
• Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction (2021) — 318 citations
• Learning to Restore Low-Light Images via Decomposition-and-Enhancement (2020) — 443 citations
• KT-GAN: Knowledge-Transfer Generative Adversarial Network for Text-to-Image Synthesis (2020) — 74 citations
• IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge. (2020) — 366 citations