Niemeijer, Joshua und Mittal, Sudhanshu und Schäfer, Jörg P. und Brox, Thomas (2023) Best Practices in Active Learning for Semantic Segmentation. In: 45th Annual Conference of the German Association for Pattern Recognition. German Conference on Pattern Recognition (GCPR), 2023-09-19 - 2023-09-22, Heidelberg. doi: 10.1007/978-3-031-54605-1_28. ISBN 978-303154604-4. ISSN 0302-9743.
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Kurzfassung
Active learning is particularly of interest for semantic segmentation, where annotations are costly. Previous academic studies focused on datasets that are already very diverse and where the model is trained in a supervised manner with a large annotation budget. In contrast, data collected in many driving scenarios is highly redundant, and most medical applications are subject to very constrained annotation budgets. This work investigates the various types of existing active learning methods for semantic segmentation under diverse conditions across three dimensions - data distribution w.r.t. different redundancy levels, integration of semi-supervised learning, and different labeling budgets. We find that these three underlying factors are decisive for the selection of the best active learning approach. As an outcome of our study, we provide a comprehensive usage guide to obtain the best performance for each case. It is the first systematic study that investigates these dimensions covering a wide range of settings including more than 3K model training runs. In this work, we also propose an exemplary evaluation task for driving scenarios, where data has high redundancy, to showcase the practical implications of our research findings.
elib-URL des Eintrags: | https://elib.dlr.de/198546/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||
Titel: | Best Practices in Active Learning for Semantic Segmentation | ||||||||||||||||||||
Autoren: |
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Datum: | September 2023 | ||||||||||||||||||||
Erschienen in: | 45th Annual Conference of the German Association for Pattern Recognition | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
DOI: | 10.1007/978-3-031-54605-1_28 | ||||||||||||||||||||
ISSN: | 0302-9743 | ||||||||||||||||||||
ISBN: | 978-303154604-4 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | Active Learning, Semantic Segmentation | ||||||||||||||||||||
Veranstaltungstitel: | German Conference on Pattern Recognition (GCPR) | ||||||||||||||||||||
Veranstaltungsort: | Heidelberg | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 19 September 2023 | ||||||||||||||||||||
Veranstaltungsende: | 22 September 2023 | ||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
HGF - Programm: | Verkehr | ||||||||||||||||||||
HGF - Programmthema: | Straßenverkehr | ||||||||||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||||||||||
DLR - Forschungsgebiet: | V ST Straßenverkehr | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz | ||||||||||||||||||||
Standort: | Berlin-Adlershof , Braunschweig | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik Institut für Verkehrssystemtechnik > Kooperative Systeme, BS Institut für Verkehrssystemtechnik > Kooperative Systeme, BA | ||||||||||||||||||||
Hinterlegt von: | Niemeijer, Joshua | ||||||||||||||||||||
Hinterlegt am: | 05 Dez 2023 14:30 | ||||||||||||||||||||
Letzte Änderung: | 21 Okt 2024 10:46 |
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