UAVs and Neural Networks for search and rescue missions

  • 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.

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  • —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 imple- mentation 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 automatically labeled images. Finally, we evaluate the performance of different neural networks.

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Metadaten
Author:Hartmut Surmann, Artur Leinweber, Gerhard Senkowski, Julien Meine, Dominik Slomma
URN:urn:nbn:de:hbz:1010-opus4-44617
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2023/10/09
Date of first Publication:2023/09/26
Publishing Institution:Westfälische Hochschule Gelsenkirchen Bocholt Recklinghausen
Release Date:2024/01/29
Pagenumber:8
First Page:1
Last Page:8
Departments / faculties:Fachbereiche / Informatik und Kommunikation
Dewey Decimal Classification:Informatik, Informationswissenschaft, allgemeine Werke / Informatik, Wissen, Systeme / Datenverarbeitung; Informatik
Licence (German):License LogoCreative Commons - Namensnennung - Keine Bearbeitung

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