TY  - CONF
A1  - Surmann, Hartmut
A1  - Leinweber, Artur
A1  - Senkowski, Gerhard
A1  - Meine, Julien
A1  - Slomma, Dominik
T1  - UAVs and Neural Networks for search and rescue missions
N2  - In this paper, we present a method for detecting objects of interest, including cars, humans, and fire, in aerial images captured by unmanned aerial vehicles (UAVs) usually during vegetation fires. To achieve this, we use artificial neural networks and create a dataset for supervised learning. We accomplish the assisted labeling of the dataset through the implementation of an object detection pipeline that combines classic image processing techniques with pretrained neural networks. In addition, we develop a data augmentation pipeline to augment the dataset with  utomatically labeled images. Finally, we evaluate the performance of different neural networks.
Y1  - 2023
UR  - https://whge.opus.hbz-nrw.de/frontdoor/index/index/docId/4461
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:1010-opus4-44617
SP  - 1
EP  - 8
ER  -