My work is at the crossroads of statistics, machine learning, image processing and computer vision. I am interested in tackling practical problems that arise in multimedia, remote sensing and robotics.
Besides that, I teach Machine Learning and Computer Vision at Institut d’Optique Graduate School (Univ. Paris Saclay) and ENSTA ParisTech (Institut Polytechnique de Paris). I also serve as Chair of the IEEE GRSS Image Analysis and Data Fusion Technical Committee.
- [July 2019] Ronny Hänsch (TU Berlin, Germany), Devis Tuia (Uni Wangeningen, NL), Yuliya Tarabalka (LuxCarta, FR) and myself will give a tutorial on Machine Learning for Remote Sensing - Best practices and recent solutions at IGARSS 2019, in Yokohama, Japan, on July 28th.
- [June 2019] Our review on deep learning models for classification of remote sensing hyperspectral data is finally published (after 2 years of much debated editorial process) in GRSM: https://doi.org/10.1109/MGRS.2019.2912563. It comes with our DeepHyperX toolbox with several SOA networks for HSI: https://github.com/nshaud/DeepHyperX
- [June 2019] The JSTARS paper about the outcome of the 2018 Data Fusion Contest that I co-organized with Ronny Hänsch (TU Berlin, Germany), Naoto Yokoya (RIKEN, JP) and Saurabh Prasad (U. of Houston, US), is out! You can get it in open-access from https://doi.org/10.1109/JSTARS.2019.2911113. Please note that testing algorithms with this dataset is still possible on the IEEE GRSS DASE website
- [June 2019] Rodrigo Caye Daudt got the Best Student Paper Award at CVPR/Earth Vision 2019. Congrats!
- [June 2019] Not exactly an early-adopter, I now have a twitter account to post news on a more regular basis.