Shreyansh Daftry

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 2 papers; trusts 115 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 30 citations into it; #12,347 of 21,575 by trust here, #12,689 by citations
• Artificial Intelligence — 22 citations into it; #18,257 of 35,345 by trust here, #18,186 by citations
• Aerospace Engineering — 10 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Shreyansh Daftry trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Stéphane Ross
4. Ilya Sutskever
5. Yann LeCun
6. Yoshua Bengio
7. Yichuan Tang
8. Jia Deng
9. Diederik P. Kingma
10. Kaiming He

Who trusts Shreyansh Daftry overall

1. Faraz Torabi
2. Vihan Jain
3. Garrett Warnell
4. Saurabh Gupta
5. Peter Stone
6. Haoshuo Huang
7. Coline Devin
8. Sergey Levine
9. Gabriel Ilharco
10. Eric Tzeng

Papers from Shreyansh Daftry's perspective

Ordered by how strongly the researchers Shreyansh Daftry 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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Learning Transferable Policies for Monocular Reactive MAV Control (2016) — 89 citations
• Introspective perception: Learning to predict failures in vision systems (2016) — 86 citations