Nicolas Dobigeon
Media Technology · 2009–2015
A researcher in the Science corpus: 7 papers; trusts 40 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 109 citations into it; #588 of 3,621 by trust here, #425 by citations
- Computer Vision and Pattern Recognition — 56 citations into it; #6,533 of 21,575 by trust here, #9,305 by citations
- Analytical Chemistry — 36 citations into it; #510 of 1,254 by trust here, #213 by citations
- Atmospheric Science — 30 citations into it
- Computational Mechanics — 30 citations into it; #3,880 of 10,001 by trust here, #7,501 by citations
- Ecology — 23 citations into it
- Biomedical Engineering — 18 citations into it
- Artificial Intelligence — 16 citations into it; #19,717 of 35,345 by trust here, #11,921 by citations
Whom Nicolas Dobigeon trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- José M. Bioucas-Dias
- Christian P. Robert
- Daniel C. Heinz
- Jose M. P. Nascimento
- Chein-I. Chang
- Stéphane Mallat
- Antonio J. Plaza
- Nirmal Keshava
- E.J. Candes
- Marian-Daniel Iordache
Who trusts Nicolas Dobigeon overall
- Renwei Dian
- Shutao Li
- Hassan Ghassemian
- José M. Bioucas-Dias
- Naoto Yokoya
- Leyuan Fang
- Rob Heylen
- Jean-Yves Tourneret
- Pedram Ghamisi
- Mario Parente
Papers from Nicolas Dobigeon's perspective
Ordered by how strongly the researchers Nicolas Dobigeon trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Regression Shrinkage and Selection via the Lasso
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Atomic Decomposition by Basis Pursuit
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- A wavelet tour of signal processing
- Gradient-based learning applied to document recognition
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Vertex component analysis: a fast algorithm to unmix hyperspectral data (IEEE Transactions on Geoscience and Remote Sensing)
Their papers
- Hyperspectral Pansharpening: A Review (2015) — 778 citations
- Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation (2015) — 468 citations
- Hyperspectral and Multispectral Image Fusion Based on a Sparse Representation (2014) — 568 citations
- Nonlinear Unmixing of Hyperspectral Images: Models and Algorithms (2013) — 453 citations
- Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches (2012) — 2,769 citations
- Nonlinear unmixing of hyperspectral images using a generalized bilinear model (2011) — 460 citations
- Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery (2009) — 390 citations