Subhasis Chaudhuri
Artificial Intelligence · 2004–2022
A researcher in the Science corpus: 5 papers; trusts 397 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 88 citations into it; #28,686 of 35,345 by trust here, #32,362 by citations
- Computer Vision and Pattern Recognition — 80 citations into it; #11,612 of 21,575 by trust here, #17,757 by citations
- Meta & Continual Learning — 45 citations into it
- Representation & Self-Supervised Learning — 40 citations into it
- Radiology, Nuclear Medicine and Imaging — 15 citations into it
- Optimization & Training — 10 citations into it
- Media Technology — 9 citations into it; #1,366 of 3,621 by trust here, #2,954 by citations
- Efficiency & Compression — 7 citations into it
Whom Subhasis Chaudhuri trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- Yoshua Bengio
- Kaiming He
- Yann LeCun
- Ilya Sutskever
- Andrew Zisserman
- Ross B. Girshick
- Jimmy Ba
Who trusts Subhasis Chaudhuri overall
- Mark A. Davenport
- Martin Benning
- Ali Ahmed
- Justin K. Romberg
- Martin Burger
- B. Recht
- Valerio Marsocci
- Jaya Kalla
- Ce Liu
Papers from Subhasis Chaudhuri's perspective
Ordered by how strongly the researchers Subhasis Chaudhuri trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Blind Image Deconvolution (2014) — 306 citations
- Semantics-Driven Generative Replay for Few-Shot Class Incremental Learning (2022) — 42 citations
- SemGIF: A Semantics Guided Incremental Few-shot Learning Framework with Generative Replay (2021) — 3 citations
- CILEA-NET: Curriculum-Based Incremental Learning Framework for Remote Sensing Image Classification (2021) — 24 citations
- Content based image retrieval using motif cooccurrence matrix (2004) — 308 citations