Yimian Dai

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 381 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 100 citations into it
• Artificial Intelligence — 57 citations into it
• Model Architectures — 41 citations into it
• Aerospace Engineering — 25 citations into it; #605 of 6,421 by trust here, #3,519 by citations
• Electrical and Electronic Engineering — 15 citations into it; #2,126 of 16,539 by trust here, #13,165 by citations
• Optimization & Training — 10 citations into it
• Computational Mechanics — 9 citations into it
• Media Technology — 9 citations into it; #2,596 of 3,621 by trust here, #2,820 by citations

Whom Yimian Dai trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Ross B. Girshick
4. Geoffrey E. Hinton
5. Shaoqing Ren
6. Christian Szegedy
7. X. Zhang
8. Yoshua Bengio
9. Tsung-Yi Lin
10. Yann LeCun

Who trusts Yimian Dai overall

1. Xin Wu
2. Landan Zhang
3. Boyang Li
4. Tianfang Zhang
5. Mingjin Zhang
6. Danfeng Hong
7. Zhenming Peng
8. Yang Sun
9. Huan Wang
10. Yiquan Wu

Papers from Yimian Dai's perspective

Ordered by how strongly the researchers Yimian Dai 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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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

• Reweighted Infrared Patch-Tensor Model With Both Nonlocal and Local Priors for Single-Frame Small Target Detection (2017) — 547 citations
• Attentional Feature Fusion (2020) — 979 citations
• Asymmetric Contextual Modulation for Infrared Small Target Detection (2020) — 723 citations
• Attentional Local Contrast Networks for Infrared Small Target Detection (2020) — 744 citations