Philippe Giguère
Computer Vision and Pattern Recognition · 2015–2022
A researcher in the Science corpus: 6 papers; trusts 379 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 99 citations into it
- Aerospace Engineering — 52 citations into it
- Artificial Intelligence — 33 citations into it
- Geology — 12 citations into it
- Reinforcement Learning — 11 citations into it
- Environmental Engineering — 8 citations into it
- Model Architectures — 8 citations into it
Whom Philippe Giguère trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Shaoqing Ren
- Ross B. Girshick
- X. Zhang
- Ilya Sutskever
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
Papers from Philippe Giguère's perspective
Ordered by how strongly the researchers Philippe Giguère 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
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Deep Template-based Object Instance Detection (2021) — 31 citations
- Instance Segmentation for Autonomous Log Grasping in Forestry Operations (2022) — 38 citations
- ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals (2019) — 397 citations
- SuMa++: Efficient LiDAR-based Semantic SLAM (2019) — 555 citations
- Tree Species Identification from Bark Images Using Convolutional Neural Networks (2018) — 72 citations
- Learning legged swimming gaits from experience (2015) — 41 citations