UAVs and Neural Networks for search and rescue missions

Autor:	Surmann, Hartmut, Leinweber, Artur, Senkowski, Gerhard, Meine, Julien, Slomma, Dominik
Rok vydání:	2023
Předmět:	Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	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 automatically labeled images. Finally, we evaluate the performance of different neural networks. Comment: 8 pages, 56th International Symposium on Robotics (ISR Europe) | September 26-27, 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2310.05512 Zobrazit plný text záznamu View this record from Arxiv