Harsh Agarwal

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 47 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 36 citations into it
• Aerospace Engineering — 13 citations into it

Whom Harsh Agarwal trusts overall

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

1. David G. Lowe
2. Diederik P. Kingma
3. Kaiming He

Papers from Harsh Agarwal's perspective

Ordered by how strongly the researchers Harsh Agarwal 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Et al
5. Histograms of oriented gradients for human detection
6. Distinctive Image Features from Scale-Invariant Keypoints
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction (2018) — 694 citations