Salman Khan

Computer Vision and Pattern Recognition · with Muhammad · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 49 citations into it
• Artificial Intelligence — 35 citations into it
• Model Architectures — 9 citations into it
• Media Technology — 6 citations into it

Whom Salman Khan trusts overall

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

1. Alex Krizhevsky
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Christian Szegedy
5. Ilya Sutskever
6. Diederik P. Kingma
7. Andrew Zisserman
8. Kaiming He
9. Yangqing Jia
10. Yoshua Bengio

Papers from Salman Khan's perspective

Ordered by how strongly the researchers Salman Khan 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. ImageNet Large Scale Visual Recognition Challenge
6. Going deeper with convolutions
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Multi-grade brain tumor classification using deep CNN with extensive data augmentation (2019) — 782 citations
• Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey (2020) — 325 citations