Élisa Fromont

Computer Vision and Pattern Recognition · 2007–2020

A researcher in the Science corpus: 5 papers; trusts 451 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 62 citations into it; #13,158 of 21,575 by trust here, #10,905 by citations
• Artificial Intelligence — 34 citations into it; #5,761 of 35,345 by trust here, #16,771 by citations
• Information Systems — 11 citations into it; #693 of 8,771 by trust here, #3,098 by citations
• Model Architectures — 10 citations into it
• Computational Theory and Mathematics — 9 citations into it; #1,148 of 12,182 by trust here, #3,562 by citations
• Media Technology — 9 citations into it
• Algorithms & Complexity — 8 citations into it; #146 of 516 by trust here, #229 by citations
• Evaluation & Benchmarks — 7 citations into it

Whom Élisa Fromont trusts overall

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

1. Andrew Zisserman
2. Karen Simonyan
3. David G. Lowe
4. Rakesh Agrawal
5. Kaiming He
6. Geoffrey E. Hinton
7. Alex Krizhevsky
8. Yann LeCun
9. Yoshua Bengio
10. Ross B. Girshick

Who trusts Élisa Fromont overall

1. Emir Demirovi'c
2. Gaël Aglin
3. Cynthia Rudin
4. Siegfried Nijssen
5. Yiming Sun
6. Vinícius G. Costa
7. Jifeng Shen
8. Anna Lukina
9. Sina Aghaei
10. Gong Cheng

Papers from Élisa Fromont's perspective

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

Their papers

• Residual Conv-Deconv Grid Network for Semantic Segmentation (2017) — 238 citations
• Optimal constraint-based decision tree induction from itemset lattices (2010) — 72 citations
• Mining optimal decision trees from itemset lattices (2007) — 92 citations
• Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks (2020) — 311 citations
• Mining Mid-level Features for Image Classification (2014) — 86 citations