Trung T. Pham

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 6 papers; trusts 410 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 95 citations into it; #12,501 of 21,575 by trust here, #8,122 by citations
• Artificial Intelligence — 33 citations into it; #19,995 of 35,345 by trust here, #14,181 by citations
• Aerospace Engineering — 18 citations into it
• Generative Models — 8 citations into it
• Model Architectures — 7 citations into it
• Representation & Self-Supervised Learning — 6 citations into it; #2,160 of 3,145 by trust here, #1,913 by citations
• Signal Processing — 5 citations into it

Whom Trung T. Pham trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Yann LeCun
6. Andrew Zisserman
7. Shaoqing Ren
8. Piotr Doll'ar
9. Pablo Arbeláez
10. Yoshua Bengio

Who trusts Trung T. Pham overall

1. Ekin Dogus Cubuk
2. Barret Zoph
3. Ping Hu
4. Seyed Hamid Rezatofighi
5. Yang Liu
6. B. V. Kumar
7. Tong Niu
8. Raul Mur-Artal
9. Shuxiao Chen
10. Stan Sclaroff

Papers from Trung T. Pham's perspective

Ordered by how strongly the researchers Trung T. Pham 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
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

• A Bayesian Data Augmentation Approach for Learning Deep Models (2017) — 245 citations
• Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge (2017) — 147 citations
• Bayesian Semantic Instance Segmentation in Open Set World (2018) — 35 citations
• Efficient Point Process Inference for Large-Scale Object Detection (2016) — 24 citations
• Meaningful maps with object-oriented semantic mapping (2016) — 228 citations
• The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research (2016) — 83 citations