Umme Zahoora

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 361 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 133 citations into it
• Artificial Intelligence — 93 citations into it
• Model Architectures — 48 citations into it
• Natural Language Processing — 15 citations into it
• Signal Processing — 13 citations into it
• Optimization & Training — 11 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Umme Zahoora trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Alex Krizhevsky
5. Ross B. Girshick
6. Kaiming He
7. Ilya Sutskever
8. Ruslan Salakhutdinov
9. Diederik P. Kingma
10. Sepp Hochreiter

Papers from Umme Zahoora's perspective

Ordered by how strongly the researchers Umme Zahoora 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A survey of the recent architectures of deep convolutional neural networks (2019) — 2,740 citations