@inproceedings{3f851f74eecb456fbc0092bc24205350,
title = "ARTIFIVE-POTSDAM: A BENCHMARK FOR LEARNING WITH ARTIFICIAL OBJECTS FOR IMPROVED AERIAL VEHICLE DETECTION",
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.",
keywords = "Artificial data, Benchmark, Machine learning, Vehicle detection",
author = "Immanuel Weber and Jens Bongartz and Ribana Roscher",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",
year = "2021",
doi = "10.1109/IGARSS47720.2021.9553162",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1214--1217",
booktitle = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
}