Mathieu Fauvel
Media Technology · 2008–2013
A researcher in the Science corpus: 5 papers; trusts 36 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 49 citations into it; #334 of 3,621 by trust here, #161 by citations
- Computer Vision and Pattern Recognition — 33 citations into it; #12,083 of 21,575 by trust here, #8,296 by citations
- Atmospheric Science — 30 citations into it; #225 of 4,804 by trust here, #303 by citations
- Artificial Intelligence — 26 citations into it
- Analytical Chemistry — 24 citations into it; #878 of 1,254 by trust here, #148 by citations
- Statistical Learning Theory — 14 citations into it
- Ecology — 7 citations into it; #9,564 of 10,717 by trust here, #6,543 by citations
- Probabilistic & Bayesian Methods — 5 citations into it
Whom Mathieu Fauvel trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jon Atli Benediktsson
- David A. Landgrebe
- Martino Pesaresi
- Lorenzo Bruzzone
- Yuhai Wu
- C. Burges
- Farid Melgani
- Gustau Camps-Valls
- Vladimir Naumovich Vapni
- Klaus Nordhausen
Who trusts Mathieu Fauvel overall
- Jun Yu Li
- Pedram Ghamisi
- Jon Atli Benediktsson
- Xin Huang
- Yushi Chen
- Lin He
- M. Dalla Mura
- Xudong Kang
- Shutao Li
- Liangpei Zhang
Papers from Mathieu Fauvel's perspective
Ordered by how strongly the researchers Mathieu Fauvel trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- The Nature of Statistical Learning Theory
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
Their papers
- Advances in Spectral-Spatial Classification of Hyperspectral Images (2013) — 1,259 citations
- SVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images (2010) — 730 citations
- Kernel Principal Component Analysis for the Classification of Hyperspectral Remote Sensing Data over Urban Areas (2009) — 296 citations
- Recent Advances in Techniques for Hyperspectral Image Processing (2009) — 1,721 citations
- Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles (2008) — 1,156 citations