Jennifer Grannen

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 16 citations into it

Whom Jennifer Grannen trusts overall

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

1. Gregory R. Koch
2. Ken Perlin
3. Kaiming He
4. David G. Lowe

Papers from Jennifer Grannen's perspective

Ordered by how strongly the researchers Jennifer Grannen 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. Histograms of oriented gradients for human detection
4. Distinctive Image Features from Scale-Invariant Keypoints
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Mask R-CNN
10. Long Short-Term Memory

Their papers

• Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data (2020) — 145 citations