Maximiliam Seitz

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 25 citations into it

Whom Maximiliam Seitz trusts overall

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

1. Kaiming He

Papers from Maximiliam Seitz's perspective

Ordered by how strongly the researchers Maximiliam Seitz 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. Going deeper with convolutions
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Fully convolutional networks for semantic segmentation
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Long Short-Term Memory

Their papers

• Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild (2019) — 486 citations