Pravendra Singh

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 4 papers; trusts 818 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 139 citations into it; #9,372 of 21,575 by trust here, #11,498 by citations
• Artificial Intelligence — 120 citations into it; #14,488 of 35,345 by trust here, #17,776 by citations
• Representation & Self-Supervised Learning — 44 citations into it
• Meta & Continual Learning — 41 citations into it; #381 of 1,041 by trust here, #470 by citations
• Automotive Engineering — 39 citations into it
• Reinforcement Learning — 20 citations into it
• Aerospace Engineering — 18 citations into it
• Evaluation & Benchmarks — 16 citations into it

Whom Pravendra Singh trusts overall

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

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

Who trusts Pravendra Singh overall

1. Da-Wei Zhou
2. Chang-Bin Zhang
3. Gyuhak Kim
4. Prashant Bhat
5. Haiyan Yin
6. Jianqiang Xiao
7. Eden Belouadah
8. Han-Jia Ye
9. Qiwen Wang
10. Liyuan Wang

Papers from Pravendra Singh's perspective

Ordered by how strongly the researchers Pravendra Singh 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Recent Advancements in End-to-End Autonomous Driving Using Deep Learning: A Survey (2023) — 310 citations
• Few-Shot Lifelong Learning (2021) — 159 citations
• Rectification-based Knowledge Retention for Continual Learning (2021) — 51 citations
• Calibrating CNNs for Lifelong Learning (2020) — 78 citations