Eugene Vorontsov
Computer Vision and Pattern Recognition · 2016–2021
A researcher in the Science corpus: 6 papers; trusts 26 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 54 citations into it; #12,774 of 21,575 by trust here, #3,747 by citations
- Artificial Intelligence — 53 citations into it; #20,515 of 35,345 by trust here, #5,880 by citations
- Model Architectures — 26 citations into it; #1,421 of 2,278 by trust here, #842 by citations
- Optimization & Training — 9 citations into it; #1,989 of 2,601 by trust here, #1,448 by citations
Whom Eugene Vorontsov trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- Geoffrey E. Hinton
- Yoshua Bengio
- Mikael Henaff
- Sepp Hochreiter
- Kaiming He
- Xavier Glorot
- Vinod Nair
- Quoc V. Le
- J. Urgen Schmidhuber
Who trusts Eugene Vorontsov overall
- Lei Huang
- Benjamin Ehret
- Mario Lezcano Casado
- Piotr A. Sokól
- Zhi Chen
- Jun Li
- Meenal Narkhede
- Yuto Ashida
- Zakaria Mhammedi
- Fabian Isensee
Papers from Eugene Vorontsov's perspective
Ordered by how strongly the researchers Eugene Vorontsov trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- The Liver Tumor Segmentation Benchmark (LiTS) (2019) — 1,500 citations
- On orthogonality and learning recurrent networks with long term dependencies (2017) — 265 citations
- The Medical Segmentation Decathlon (2021) — 1,513 citations
- A large annotated medical image dataset for the development and evaluation of segmentation algorithms (2019) — 1,013 citations
- The Importance of Skip Connections in Biomedical Image Segmentation (2016) — 1,139 citations
- Deep Learning: A Primer for Radiologists. (2017) — 1,015 citations