Nibaran Das

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 609 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 122 citations into it
• Artificial Intelligence — 38 citations into it
• Model Architectures — 19 citations into it
• Optimization & Training — 6 citations into it
• Aerospace Engineering — 5 citations into it
• Biomedical Engineering — 5 citations into it
• Biophysics — 5 citations into it

Whom Nibaran Das trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yann LeCun
6. Yoshua Bengio
7. Diederik P. Kingma
8. Ilya Sutskever
9. Shaoqing Ren
10. Liang-Chieh Chen

Papers from Nibaran Das's perspective

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

Their papers

• Understanding Deep Learning Techniques for Image Segmentation (2019) — 440 citations