Walter Forkel

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 17 citations into it
• Artificial Intelligence — 15 citations into it
• Model Architectures — 7 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Walter Forkel trusts overall

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

1. Geoffrey E. Hinton
2. Karen Simonyan
3. Alan L. Yuille
4. Alex Krizhevsky
5. Kaiming He
6. Yann LeCun
7. Andrew Zisserman
8. Ross B. Girshick
9. Liang-Chieh Chen
10. Yoshua Bengio

Papers from Walter Forkel's perspective

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

Their papers

• Efficient Likelihood Learning of a Generic CNN-CRF Model for Semantic Segmentation (2015) — 18 citations