Devinder Kumar

Computer Vision and Pattern Recognition · 2015–2017

A researcher in the Science corpus: 5 papers; trusts 176 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it; #12,406 of 21,575 by trust here, #13,815 by citations
• Artificial Intelligence — 26 citations into it; #19,881 of 35,345 by trust here, #20,377 by citations
• Safety, Robustness & Interpretability — 13 citations into it; #1,523 of 2,251 by trust here, #2,014 by citations
• Biophysics — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Natural Language Processing — 5 citations into it

Whom Devinder Kumar trusts overall

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

1. Karen Simonyan
2. Matthew D. Zeiler
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Quoc V. Le
6. Alex Krizhevsky
7. Yann LeCun
8. Andrew Zisserman
9. Rob Fergus
10. Diederik P. Kingma

Who trusts Devinder Kumar overall

1. Quanshi Zhang
2. A. Asuntha
3. Jingjing Chen
4. Wafaa Alakwaa
5. Maciej A. Mazurowski
6. Chaopeng Shen
7. Min Chen
8. Douwe Kiela
9. Yutong Xie
10. Alun David Preece

Papers from Devinder Kumar's perspective

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

Their papers

• Recipe recognition with large multimodal food dataset (2015) — 259 citations
• Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks (2017) — 63 citations
• Insightful classification of crystal structures using deep learning (2017) — 323 citations
• Opening the Black Box of Financial AI with CLEAR-Trade: A CLass-Enhanced Attentive Response Approach for Explaining and Visualizing Deep Learning-Driven Stock Market Prediction (2017) — 21 citations
• Lung Nodule Classification Using Deep Features in CT Images (2015) — 330 citations