Saumik Bhattacharya

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Artificial Intelligence — 8 citations into it
• Media Technology — 6 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Saumik Bhattacharya trusts overall

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

1. Lina Karam
2. Yann LeCun
3. Alex Krizhevsky
4. Christian Szegedy
5. Geoffrey E. Hinton
6. Samuel F. Dodge

Papers from Saumik Bhattacharya's perspective

Ordered by how strongly the researchers Saumik Bhattacharya 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. Gradient-based learning applied to document recognition
3. ImageNet: A large-scale hierarchical image database
4. Learning Multiple Layers of Features from Tiny Images
5. ImageNet classification with deep convolutional neural networks
6. Microsoft COCO: Common Objects in Context
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet Large Scale Visual Recognition Challenge
9. Rethinking the Inception Architecture for Computer Vision
10. Long Short-Term Memory

Their papers

• Effects of Degradations on Deep Neural Network Architectures (2018) — 167 citations