Shiv Ram Dubey

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 4 papers; trusts 1,403 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 147 citations into it; #19,323 of 21,575 by trust here, #20,756 by citations
• Artificial Intelligence — 75 citations into it
• Model Architectures — 34 citations into it
• Media Technology — 22 citations into it; #3,555 of 3,621 by trust here, #2,954 by citations
• Representation & Self-Supervised Learning — 17 citations into it
• Optimization & Training — 13 citations into it
• Evaluation & Benchmarks — 11 citations into it
• Atmospheric Science — 10 citations into it; #4,641 of 4,804 by trust here, #4,137 by citations

Whom Shiv Ram Dubey trusts overall

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

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

Who trusts Shiv Ram Dubey overall

1. Swalpa Kumar Roy

Papers from Shiv Ram Dubey's perspective

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

Their papers

• Activation functions in deep learning: A comprehensive survey and benchmark (2021) — 1,138 citations
• A Decade Survey of Content Based Image Retrieval Using Deep Learning (2020) — 329 citations
• HybridSN: Exploring 3-D–2-D CNN Feature Hierarchy for Hyperspectral Image Classification (2019) — 1,500 citations
• Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image Classification (2019) — 496 citations