Minh-Khoi Tran

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 5 papers; trusts 421 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 104 citations into it; #9,288 of 21,575 by trust here, #8,021 by citations
• Aerospace Engineering — 48 citations into it; #1,656 of 6,421 by trust here, #1,175 by citations
• Computational Mechanics — 33 citations into it; #2,499 of 10,001 by trust here, #1,325 by citations
• 3D Vision & Pose — 32 citations into it; #418 of 689 by trust here, #421 by citations
• Geology — 28 citations into it; #338 of 687 by trust here, #226 by citations
• Computer Graphics and Computer-Aided Design — 19 citations into it
• Artificial Intelligence — 15 citations into it
• Evaluation & Benchmarks — 9 citations into it; #1,733 of 3,147 by trust here, #1,921 by citations

Whom Minh-Khoi Tran trusts overall

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

1. Karen Simonyan
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Kaiming He
5. Alex Krizhevsky
6. Andrew Zisserman
7. Yann LeCun
8. Shuran Song
9. Yoshua Bengio
10. Pedro F. Felzenszwalb

Who trusts Minh-Khoi Tran overall

1. Quang-Hieu Pham
2. Binh-Son Hua
3. Dinh C. Nguyen
4. Angela Dai
5. Saifullahi Aminu Bello
6. Zaiwei Zhang
7. Jens Behley
8. Benjamin Ummenhofer
9. Thang Vu
10. Hugues Thomas

Papers from Minh-Khoi Tran's perspective

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

Their papers

• SceneNN: A Scene Meshes Dataset with aNNotations (2016) — 406 citations
• A Field Model for Repairing 3D Shapes (2016) — 122 citations
• RGB-D Object-to-CAD Retrieval (2018) — 18 citations
• Pointwise Convolutional Neural Networks (2017) — 587 citations
• RGB-D to CAD Retrieval with ObjectNN Dataset (2017) — 20 citations