ARTIFIVE-POTSDAM: A BENCHMARK FOR LEARNING WITH ARTIFICIAL OBJECTS FOR IMPROVED AERIAL VEHICLE DETECTION

Immanuel Weber, Jens Bongartz, Ribana Roscher

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)

Abstract

In order to enable the development of powerful machine learning methods for remote sensing-based Earth observation tasks, benchmarks are needed to evaluate the methods and compare them to other methods comprehensively. We present ArtifiVe-Potsdam, a freely available dataset that is targeting vehicle detection in aerial imagery. In particular, the benchmark focuses on enriching real datasets with artificial data and quantifying the added value. The dataset aims to stimulate research on the efficient and cost-effective creation and enrichment of datasets for remote sensing since datasets with a limited number of labels are common and the collection of data and labels is time-consuming and expensive.

OriginalspracheEnglisch
TitelIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten1214-1217
Seitenumfang4
ISBN (elektronisch)9781665403696
DOIs
PublikationsstatusVeröffentlicht - 2021
Extern publiziertJa
Veranstaltung2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgien
Dauer: 12 Juli 202116 Juli 2021

Publikationsreihe

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Band2021-July

Konferenz

Konferenz2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Land/GebietBelgien
OrtBrussels
Zeitraum12/07/2116/07/21

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