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Konen, Kai and Hecking, Tobias (2022) Using Synthetic Images to Evaluate and Improve Object Detection Neural Networks Performance on Aerial Image Datasets. International Journal of Semantic Computing, 16 (3), pp. 339-356. World Scientific. doi: 10.1142/S1793351X22420016. ISSN 1793-351X.
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Official URL: https://doi.org/10.1142/S1793351X22420016
| Item URL in elib: | https://elib.dlr.de/186808/ | |||||||||
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| Document Type: | Article | |||||||||
| Title: | Using Synthetic Images to Evaluate and Improve Object Detection Neural Networks Performance on Aerial Image Datasets | |||||||||
| Authors: |
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| Date: | 2022 | |||||||||
| Journal or Publication Title: | International Journal of Semantic Computing | |||||||||
| Refereed publication: | Yes | |||||||||
| Open Access: | No | |||||||||
| Gold Open Access: | No | |||||||||
| In SCOPUS: | Yes | |||||||||
| In ISI Web of Science: | Yes | |||||||||
| Volume: | 16 | |||||||||
| DOI : | 10.1142/S1793351X22420016 | |||||||||
| Page Range: | pp. 339-356 | |||||||||
| Publisher: | World Scientific | |||||||||
| ISSN: | 1793-351X | |||||||||
| Status: | Published | |||||||||
| Keywords: | UAV, Object Detection, Neural Networks, Aerial Images, Synthetic Images, Simulation | |||||||||
| HGF - Research field: | Aeronautics, Space and Transport | |||||||||
| HGF - Program: | Aeronautics | |||||||||
| HGF - Program Themes: | Components and Systems | |||||||||
| DLR - Research area: | Aeronautics | |||||||||
| DLR - Program: | L CS - Components and Systems | |||||||||
| DLR - Research theme (Project): | L - Unmanned Aerial Systems | |||||||||
| Location: | Köln-Porz | |||||||||
| Institutes and Institutions: | Institute for Software Technology > Intelligent and Distributed Systems Institute for Software Technology | |||||||||
| Deposited By: | Konen, Kai | |||||||||
| Deposited On: | 11 Aug 2022 10:50 | |||||||||
| Last Modified: | 19 Aug 2022 09:32 |
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