Prieur, Colin und Ait Ali Braham, Nassim und Tresson, Paul und Vincent, Grégoire und Chanussot, Jocelyn (2024) Prospects for Mitigating Spectral Variability in Tropical Species Classification Using Self-Supervised Learning. In: Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS. IEEE. 2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2024-12-09 - 2024-12-11, Helsinki. doi: 10.1109/WHISPERS65427.2024.10876523.
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Offizielle URL: https://www.ieee-whispers.com/product/whispers-2024
Kurzfassung
Airborne hyperspectral imaging is a promising method for identifying tropical species, but spectral variability between acquisitions hinders consistent results. This paper proposes using Self-Supervised Learning (SSL) to encode spectral features that are robust to abiotic variability and relevant for species identification. By employing the state-of-the-art Barlow-Twins approach on repeated spectral acquisitions, we demonstrate the ability to develop stable features. For the classification of 40 tropical species, experiments show that these features can outperform typical reflectance products in terms of robustness to spectral variability by 10 points of accuracy across dates.
elib-URL des Eintrags: | https://elib.dlr.de/212955/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vorlesung) | ||||||||||||||||||||||||
Titel: | Prospects for Mitigating Spectral Variability in Tropical Species Classification Using Self-Supervised Learning | ||||||||||||||||||||||||
Autoren: |
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Datum: | Dezember 2024 | ||||||||||||||||||||||||
Erschienen in: | Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||
DOI: | 10.1109/WHISPERS65427.2024.10876523 | ||||||||||||||||||||||||
Verlag: | IEEE | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | Reflectivity, Accuracy, Conferences, Buildings, Self-supervised learning, Signal processing, Robustness, Remote sensing, Hyperspectral imaging | ||||||||||||||||||||||||
Veranstaltungstitel: | 2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) | ||||||||||||||||||||||||
Veranstaltungsort: | Helsinki | ||||||||||||||||||||||||
Veranstaltungsart: | Workshop | ||||||||||||||||||||||||
Veranstaltungsbeginn: | 9 Dezember 2024 | ||||||||||||||||||||||||
Veranstaltungsende: | 11 Dezember 2024 | ||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Künstliche Intelligenz, R - Optische Fernerkundung | ||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||||||||||||||
Hinterlegt von: | Ait Ali Braham, Nassim | ||||||||||||||||||||||||
Hinterlegt am: | 11 Mär 2025 13:29 | ||||||||||||||||||||||||
Letzte Änderung: | 11 Mär 2025 13:29 |
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