Kerekes, David und Yu, Fuxun und Klemmer, Konstantin und Albrecht, Conrad M (2026) Tutorial: A Hands-On Introduction to Benchmarking Neural Compression and Representation Learning for Earth Observation. 2026 IGARSS, 2026-08-09, Washington, DC, USA.
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Kurzfassung
This tutorial provides an introduction and hands-on session to NeuCo-Bench, https://github.com/embed2scale/NeuCo-Bench/tree/main , a benchmark framework that spun from the 2025 CVPR EARTHVISION workshop, https://www.grss-ieee.org/events/earthvision-2025/?tab=challenge . We designed NeuCo-Bench as an extendable, community-driven framework to evaluate neural compression and representation learning methods in the context of Earth Observation (EO) without the need for heavy compute resources. The growing volume and complexity of EO data calls for standardized, scalable, and reproducible tools that can assess the quality and utility of learned representations across diverse downstream tasks. NeuCo-Bench and its associated Earth2Vec community (https://earth2vec.github.io) that grew out of the Horizon Europe project Embed2Scale (https://embed2scale.eu) address this gap by offering a modular evaluation pipeline built around fixed-size, task-agnostic embeddings, enabling researchers and practitioners to consistently compare neural compression methods.
| elib-URL des Eintrags: | https://elib.dlr.de/221529/ | ||||||||||||||||||||
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| Dokumentart: | Konferenzbeitrag (Vorlesung, Vortrag) | ||||||||||||||||||||
| Titel: | Tutorial: A Hands-On Introduction to Benchmarking Neural Compression and Representation Learning for Earth Observation | ||||||||||||||||||||
| Autoren: |
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| Datum: | 2026 | ||||||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||||||
| Open Access: | Nein | ||||||||||||||||||||
| Gold Open Access: | Nein | ||||||||||||||||||||
| In SCOPUS: | Nein | ||||||||||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||||||||||
| Status: | akzeptierter Beitrag | ||||||||||||||||||||
| Stichwörter: | neural compression, EO representation learning, self-supervised learning, benchmarking, tutorial, NeuCo-Bench, embeddings, geospatial foundation models | ||||||||||||||||||||
| Veranstaltungstitel: | 2026 IGARSS | ||||||||||||||||||||
| Veranstaltungsort: | Washington, DC, USA | ||||||||||||||||||||
| Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
| Veranstaltungsdatum: | 9 August 2026 | ||||||||||||||||||||
| Veranstalter : | IEEE GRSS | ||||||||||||||||||||
| 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 - Optische Fernerkundung, R - KIPS | Künstliche Intelligenz für die Produktsicherung | ||||||||||||||||||||
| Standort: | Oberpfaffenhofen | ||||||||||||||||||||
| Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||||||||||
| Hinterlegt von: | Albrecht, Conrad M | ||||||||||||||||||||
| Hinterlegt am: | 08 Jan 2026 12:17 | ||||||||||||||||||||
| Letzte Änderung: | 08 Jan 2026 12:17 |
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