Wooram Choi

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 406 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Artificial Intelligence — 29 citations into it
• Civil and Structural Engineering — 17 citations into it; #887 of 6,160 by trust here, #822 by citations
• Model Architectures — 15 citations into it
• Optimization & Training — 13 citations into it
• Ocean Engineering — 7 citations into it; #744 of 3,193 by trust here, #209 by citations
• Media Technology — 5 citations into it
• Signal Processing — 5 citations into it

Whom Wooram Choi trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yoshua Bengio
4. Alex Krizhevsky
5. Ross B. Girshick
6. Diederik P. Kingma
7. Yann LeCun
8. Karen Simonyan
9. Shaoqing Ren
10. Vinod Nair

Who trusts Wooram Choi overall

1. D. Dais
2. Young-Jin Cha
3. Yuqing Gao
4. Shengyuan Li
5. Billie F. Spencer Jr.
6. Sattar Dorafshan
7. Dongho Kang
8. İ. Bal
9. Khalid M. Mosalam
10. Ya-dong Xue

Papers from Wooram Choi's perspective

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

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

Their papers

• Vision-based detection of loosened bolts using the Hough transform and support vector machines (2016) — 308 citations
• SDDNet: Real-Time Crack Segmentation (2020) — 394 citations
• Autonomous Structural Visual Inspection Using Region‐Based Deep Learning for Detecting Multiple Damage Types (2018) — 1,419 citations
• Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks (2017) — 2,960 citations