Active Learning pour la classication hyperspectrale : une étude comparative

Autor: Romain Thoreau, Veronique Achard, Laurent Risser, Beatrice Berthelot, Xavier Briottet

Publikováno v: IEEE geoscience and remote sensing magazine
IEEE geoscience and remote sensing magazine, In press, 10 (3), pp.256-278. ⟨10.1109/MGRS.2022.3169947⟩

International audience; Machine learning algorithms have demonstrated impressive results for land cover mapping from hyperspectral data. To enhance the generalization capabilities of statistical models, Active Learning methods guide the annotation of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f84860df365b12e4ed861b178c8bbc1
https://hal.laas.fr/hal-03676575

Mapping of Clay Montmorillonite Abundance in Agricultural Fields Using Unmixing Methods at Centimeter Scale Hyperspectral Images

Autor: Etienne Ducasse, Karine Adeline, Audrey Hohmann, Véronique Achard, Anne Bourguignon, Gilles Grandjean, Xavier Briottet

Publikováno v: Remote Sensing, Vol 16, Iss 17, p 3211 (2024)

The composition of clay minerals in soils, and more particularly the presence of montmorillonite (as part of the smectite family), is a key factor in soil swell–shrinking as well as off–road vehicle mobility. Detecting these topsoil clay minerals

Externí odkaz: https://doaj.org/article/93ac201c9b90497eb78ca898e8de7f0a

HCl, CO, and NO vertical profiles from the Grille spectrometer on ATLAS-1

Autor: Claude Camy-Peyret, Veronique Achard, Martine De Mazière

Publikováno v: Atmospheric Sensing and Modeling II.

Vertical concentration profiles of three trace species, HCl, CO, and NO, in the middle atmosphere have been retrieved from solar occultation infrared spectra recorded by the Grille spectrometer during the ATLAS-1 mission with a spectral resolution of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2a18c5f94cd9c8624c57354db47e6666
https://doi.org/10.1117/12.228542

Using a Panchromatic Image to Improve Hyperspectral Unmixing

Autor: Simon Rebeyrol, Yannick Deville, Véronique Achard, Xavier Briottet, Stephane May

Publikováno v: Remote Sensing, Vol 12, Iss 17, p 2834 (2020)

Hyperspectral unmixing is a widely studied field of research aiming at estimating the pure material signatures and their abundance fractions from hyperspectral images. Most spectral unmixing methods are based on prior knowledge and assumptions that i

Externí odkaz: https://doaj.org/article/729a861da14f4a39a3b91886d44e1b15

Inertia-Constrained Pixel-by-Pixel Nonnegative Matrix Factorisation: A Hyperspectral Unmixing Method Dealing with Intra-Class Variability

Autor: Charlotte Revel, Yannick Deville, Véronique Achard, Xavier Briottet, Christiane Weber

Publikováno v: Remote Sensing, Vol 10, Iss 11, p 1706 (2018)

Blind source separation is a common processing tool to analyse the constitution of pixels of hyperspectral images. Such methods usually suppose that pure pixel spectra (endmembers) are the same in all the image for each class of materials. In the fra

Externí odkaz: https://doaj.org/article/aa9fb83fc0294b4e83ee62a9b7c2d8ad