Pabitra Mitra

Computer Vision and Pattern Recognition · 2002–2020

A researcher in the Science corpus: 5 papers; trusts 285 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it; #5,863 of 21,575 by trust here, #7,657 by citations
• Generative Models — 45 citations into it
• Artificial Intelligence — 33 citations into it; #6,756 of 35,345 by trust here, #9,465 by citations
• Information Systems — 12 citations into it; #3,520 of 8,771 by trust here, #4,682 by citations
• Model Architectures — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Pabitra Mitra trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Mineichi Kudo
4. Alex Krizhevsky
5. Yoshua Bengio
6. Kaiming He
7. Yann LeCun
8. Karen Simonyan
9. Ilya Sutskever
10. Sergey Ioffe

Who trusts Pabitra Mitra overall

1. Qinghua Hu
2. Huan Liu
3. Bor-Chen Kuo
4. Jingrui He
5. Adrian E. Raftery
6. Yun Li
7. Alper Ünler
8. Nazrul Hoque
9. Ahmed K. Farahat
10. Xiuping Jia

Papers from Pabitra Mitra's perspective

Ordered by how strongly the researchers Pabitra Mitra 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. GENERATIVE ADVERSARIAL NETS
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Unsupervised Feature Selection Using Feature Similarity (2002) — 1,519 citations
• Data mining in soft computing framework: a survey (2002) — 720 citations
• Prior Guided GAN Based Semantic Inpainting (2020) — 101 citations
• Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network (2017) — 10 citations
• Web mining in soft computing framework: relevance, state of the art and future directions (2002) — 393 citations