Syed Afaq Ali Shah

Computer Vision and Pattern Recognition · 2013–2018

A researcher in the Science corpus: 2 papers; trusts 66 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 70 citations into it; #20,409 of 21,575 by trust here, #15,162 by citations

Whom Syed Afaq Ali Shah trusts overall

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

1. Andrew E. Johnson
2. Kevin Lai
3. Geoffrey E. Hinton
4. Kaiming He
5. Jan Knopp
6. Martial Hebert
7. Ross B. Girshick
8. Alex Krizhevsky
9. David G. Lowe
10. Ajmal Saeed Mian

Who trusts Syed Afaq Ali Shah overall

1. Salman Hameed Khan

Papers from Syed Afaq Ali Shah's perspective

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

Their papers

• A Guide to Convolutional Neural Networks for Computer Vision (2018) — 617 citations
• 3D-Div: A novel local surface descriptor for feature matching and pairwise range image registration (2013) — 22 citations