Shadab Khan

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 116 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 36 citations into it
• Artificial Intelligence — 25 citations into it; #31,871 of 35,345 by trust here, #31,361 by citations
• Radiology, Nuclear Medicine and Imaging — 9 citations into it
• Optimization & Training — 8 citations into it
• Aerospace Engineering — 7 citations into it
• Model Architectures — 7 citations into it
• Generative Models — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Shadab Khan trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Du Q. Huynh
6. A. Gholipour
7. Diederik P. Kingma
8. Andrew Zisserman
9. Ross B. Girshick
10. X. Zhang

Who trusts Shadab Khan overall

1. Arvid Lundervold

Papers from Shadab Khan's perspective

Ordered by how strongly the researchers Shadab Khan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Towards Robust and Reproducible Active Learning using Neural Networks (2020) — 89 citations
• Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration (2018) — 123 citations