Bertrand Le Saux

Computer Vision and Pattern Recognition · 2016–2022

A researcher in the Science corpus: 10 papers; trusts 742 researchers and is trusted by 60 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 149 citations into it; #6,174 of 21,575 by trust here, #8,122 by citations
• Media Technology — 81 citations into it; #335 of 3,621 by trust here, #447 by citations
• Artificial Intelligence — 66 citations into it
• Atmospheric Science — 39 citations into it; #217 of 4,804 by trust here, #827 by citations
• Model Architectures — 32 citations into it
• Aerospace Engineering — 26 citations into it
• Geology — 22 citations into it; #413 of 687 by trust here, #407 by citations
• Environmental Engineering — 19 citations into it; #879 of 5,479 by trust here, #931 by citations

Whom Bertrand Le Saux trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Karen Simonyan
4. Alex Krizhevsky
5. Yann LeCun
6. Evan Shelhamer
7. Andrew Zisserman
8. Christian Szegedy
9. Yoshua Bengio
10. Ross B. Girshick

Who trusts Bertrand Le Saux overall

1. Rodrigo Caye Daudt
2. Yuxing Chen
3. Alexandre Boulch
4. Zhenwei Shi
5. Cui Zhang
6. Lorenzo Bruzzone
7. Sheng Fang
8. Danfeng Hong
9. Yuchao Feng
10. Xu Peng

Papers from Bertrand Le Saux's perspective

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

Their papers

• Fully Convolutional Siamese Networks for Change Detection (2018) — 1,708 citations
• Weakly-Supervised Continual Learning for Class-Incremental Segmentation (2022) — 4 citations
• Deep Learning for Classification of Hyperspectral Data: A Comparative Review (2019) — 595 citations
• Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest (2019) — 308 citations
• Urban Change Detection for Multispectral Earth Observation Using Convolutional Neural Networks (2018) — 452 citations
• Multitask learning for large-scale semantic change detection (2018) — 409 citations
• Unstructured Point Cloud Semantic Labeling Using Deep Segmentation Networks (2017) — 329 citations
• SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks (2017) — 366 citations
• Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks (2017) — 621 citations
• Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks (2016) — 406 citations