Ashish Singh

Computer Vision and Pattern Recognition · with Jiang · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 287 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 71 citations into it
• Artificial Intelligence — 49 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Optimization & Training — 7 citations into it

Whom Ashish Singh trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Geoffrey E. Hinton
4. Piotr Doll'ar
5. Alex Krizhevsky
6. Yoshua Bengio
7. Yann LeCun
8. Andrew Zisserman
9. Diederik P. Kingma
10. Shaoqing Ren

Papers from Ashish Singh's perspective

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

Their papers

• Unsupervised Hard Example Mining from Videos for Improved Object Detection (2018) — 69 citations
• Automatic Adaptation of Object Detectors to New Domains Using Self-Training (2019) — 184 citations