Amit Agrawal

Computer Vision and Pattern Recognition · with Zhang · 2018

A researcher in the Science corpus: 1 paper; trusts 247 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 52 citations into it
• Artificial Intelligence — 28 citations into it
• Model Architectures — 12 citations into it
• Aerospace Engineering — 5 citations into it

Whom Amit Agrawal trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. David G. Lowe
5. Ross B. Girshick
6. Andrew Zisserman
7. Yann LeCun
8. Yoshua Bengio
9. Karen Simonyan
10. Ilya Sutskever

Papers from Amit Agrawal's perspective

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

Their papers

• Context Encoding for Semantic Segmentation (2018) — 1,368 citations