Gabriel Chartrand

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 36 citations into it; #18,521 of 21,575 by trust here, #6,737 by citations
• Artificial Intelligence — 31 citations into it; #30,229 of 35,345 by trust here, #7,531 by citations

Whom Gabriel Chartrand trusts overall

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

1. Kaiming He
2. Evan Shelhamer
3. Yann LeCun
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Christian Szegedy

Who trusts Gabriel Chartrand overall

1. Fabian Isensee
2. Arvid Lundervold

Papers from Gabriel Chartrand's perspective

Ordered by how strongly the researchers Gabriel Chartrand 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. Going deeper with convolutions
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Fully convolutional networks for semantic segmentation
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Long Short-Term Memory

Their papers

• The Liver Tumor Segmentation Benchmark (LiTS) (2019) — 1,500 citations
• The Importance of Skip Connections in Biomedical Image Segmentation (2016) — 1,139 citations
• Deep Learning: A Primer for Radiologists. (2017) — 1,015 citations