Dieter, Tamara and Weinmann, Andreas and Brucherseifer, Eva (2023) Generating Synthetic Data for Deep Learning-Based Drone Detection. In: AIP Conference Proceedings, 1 (2939). American Institute of Physics Conference Proceedings. 48th International Conference “Applications of Mathematics in Engineering and Economics” (AMEE'22), 2022-06-07 - 2022-06-13, Sozopol, Bulgaria. doi: 10.1063/5.0180345. ISSN 0094-243X.
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Official URL: https://pubs.aip.org/aip/acp/article/2939/1/030007/2929077/Generating-synthetic-data-for-deep-learning-based
Abstract
Drone detection is an important yet challenging task in the context of object detection. The development of robust and reliable drone detection systems requires large amounts of labeled data, especially when using deep learning (DL) models. Unfortunately, acquiring real data is expensive, time-consuming, and often limited by external factors. This makes synthetic data a promising approach to addressing data deficiencies. In this paper, we present a data generation pipeline based on Unreal Engine 4.25 and Microsoft AirSim, designed to create synthetic labeled data for drone detection using three-dimensional environments. As part of an ablation study, we investigate the potential use of synthetic data in drone detection by analyzing different training strategies, influencing factors, and data generation parameters, specifically related to the visual appearance of a drone.
Item URL in elib: | https://elib.dlr.de/193173/ | ||||||||||||||||
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Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||
Title: | Generating Synthetic Data for Deep Learning-Based Drone Detection | ||||||||||||||||
Authors: |
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Date: | 2023 | ||||||||||||||||
Journal or Publication Title: | AIP Conference Proceedings | ||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||
Open Access: | No | ||||||||||||||||
Gold Open Access: | No | ||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||
Volume: | 1 | ||||||||||||||||
DOI: | 10.1063/5.0180345 | ||||||||||||||||
Publisher: | American Institute of Physics Conference Proceedings | ||||||||||||||||
ISSN: | 0094-243X | ||||||||||||||||
Status: | Published | ||||||||||||||||
Keywords: | Drone Detection, Deep Learning, Synthetic Data | ||||||||||||||||
Event Title: | 48th International Conference “Applications of Mathematics in Engineering and Economics” (AMEE'22) | ||||||||||||||||
Event Location: | Sozopol, Bulgaria | ||||||||||||||||
Event Type: | international Conference | ||||||||||||||||
Event Start Date: | 7 June 2022 | ||||||||||||||||
Event End Date: | 13 June 2022 | ||||||||||||||||
Organizer: | Technical University of Sofia | ||||||||||||||||
HGF - Research field: | other | ||||||||||||||||
HGF - Program: | other | ||||||||||||||||
HGF - Program Themes: | other | ||||||||||||||||
DLR - Research area: | no assignment | ||||||||||||||||
DLR - Program: | no assignment | ||||||||||||||||
DLR - Research theme (Project): | no assignment | ||||||||||||||||
Location: | Rhein-Sieg-Kreis | ||||||||||||||||
Institutes and Institutions: | Institute for the Protection of Terrestrial Infrastructures > Digital Twins of Infrastructures Institute for the Protection of Terrestrial Infrastructures | ||||||||||||||||
Deposited By: | Lenhard, Tamara | ||||||||||||||||
Deposited On: | 06 Mar 2023 09:37 | ||||||||||||||||
Last Modified: | 24 Apr 2024 20:54 |
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