Michael Revow

Computer Vision and Pattern Recognition · 1994–1996

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 5 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Michael Revow trusts overall

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

1. David John Cameron MacKay
2. David G. Lowe
3. John Scott Bridle
4. Geoffrey E. Hinton
5. Arthur P. Dempster
6. Christopher K. I. Williams
7. Peter S. Dayan
8. Dana H. Ballard
9. Radford M. Neal
10. Yann LeCun

Who trusts Michael Revow overall

1. Brenden M. Lake
2. Ruslan Salakhutdinov
3. Geoffrey E. Hinton
4. Josh Tenenbaum
5. Andriy Myronenko
6. Yoshua Bengio
7. M. A. Carreira-Perpiñán
8. Sergey Levine
9. Alan L. Yuille
10. Xubo B. Song

Papers from Michael Revow's perspective

Ordered by how strongly the researchers Michael Revow 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. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Using Generative Models for Handwritten Digit Recognition (1996)
• Using a neural net to instantiate a deformable model (1994)