Dhanesh Ramachandram

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 275 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it; #12,883 of 21,575 by trust here, #11,498 by citations
• Artificial Intelligence — 27 citations into it; #20,683 of 35,345 by trust here, #17,110 by citations
• Multimodal Learning — 11 citations into it
• Signal Processing — 9 citations into it
• Biomedical Engineering — 6 citations into it
• Human-Computer Interaction — 6 citations into it
• Model Architectures — 6 citations into it

Whom Dhanesh Ramachandram trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yann LeCun
6. Hugo Larochelle
7. Ilya Sutskever
8. Oriol Vinyals
9. Kaiming He
10. Karen Simonyan

Who trusts Dhanesh Ramachandram overall

1. Arthur Douillard
2. Yangyang Guo
3. William Grant Hatcher
4. Alexandre Ram'e
5. Zhiyong Cheng
6. Siwei Yu
7. Alana de Santana Correia
8. Wei Yu
9. Jun Shu
10. Wenzhong Guo

Papers from Dhanesh Ramachandram's perspective

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

Their papers

• Deep Multimodal Learning: A Survey on Recent Advances and Trends (2017) — 980 citations