V. Devabhaktuni

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 87 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 46 citations into it
• Artificial Intelligence — 36 citations into it
• Radiology, Nuclear Medicine and Imaging — 29 citations into it
• Neurology — 9 citations into it
• Biomedical Engineering — 6 citations into it

Whom V. Devabhaktuni trusts overall

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

1. Kaiming He
2. Christian Szegedy
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Md. Zahangir Alom
6. Tom Fawcett
7. David Martin Ward Powers
8. Evan Shelhamer
9. Yoshua Bengio
10. Ross B. Girshick

Papers from V. Devabhaktuni's perspective

Ordered by how strongly the researchers V. Devabhaktuni 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. Attention is All you Need (Neural Information Processing Systems)
4. Going deeper with convolutions
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Fully convolutional networks for semantic segmentation
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications (2020) — 1,569 citations