Anjan Dutta

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 4 papers; trusts 709 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 101 citations into it; #5,353 of 21,575 by trust here, #9,722 by citations
• Artificial Intelligence — 83 citations into it; #7,357 of 35,345 by trust here, #14,181 by citations
• Representation & Self-Supervised Learning — 42 citations into it
• Radiology, Nuclear Medicine and Imaging — 18 citations into it
• Natural Language Processing — 11 citations into it
• Generative Models — 10 citations into it
• Media Technology — 8 citations into it
• Multimodal Learning — 7 citations into it

Whom Anjan Dutta trusts overall

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

1. Geoffrey E. Hinton
2. Karen Simonyan
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Kaiming He
6. Yoshua Bengio
7. Tomas Mikolov
8. Ross B. Girshick
9. Andrew Zisserman
10. Yann LeCun

Who trusts Anjan Dutta overall

1. Ayan Kumar Bhunia
2. Aneeshan Sain
3. Alexander Wang
4. Shiv Ram Dubey
5. Qing Liu
6. Pinaki Nath Chowdhury
7. Marco Federici
8. Tao A. Xiang
9. Yi-Zhe Song
10. Mengye Ren

Papers from Anjan Dutta's perspective

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

Their papers

• Learning Robust Representations via Multi-View Information Bottleneck (2020) — 345 citations
• Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-Based Image Retrieval (2019) — 162 citations
• Doodle to Search: Practical Zero-Shot Sketch-Based Image Retrieval (2019) — 212 citations
• Bookworm continual learning: beyond zero-shot learning and continual learning (2020) — 6 citations