Onkar Dabeer

Artificial Intelligence · 2009–2023

A researcher in the Science corpus: 3 papers; trusts 163 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 68 citations into it
• Computer Vision and Pattern Recognition — 57 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Computer Networks and Communications — 10 citations into it

Whom Onkar Dabeer trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Paul Bergmann
5. Ross B. Girshick
6. Yoshua Bengio
7. Ilya Sutskever
8. Diederik P. Kingma
9. Tsung-Yi Lin
10. Yann LeCun

Who trusts Onkar Dabeer overall

1. Jianhua Mo
2. Robert W. Heath

Papers from Onkar Dabeer's perspective

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

Their papers

• On the limits of communication with low-precision analog-to-digital conversion at the receiver (2009) — 370 citations
• WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation (2023) — 563 citations
• SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation (2022) — 729 citations