AFAS-YOLOv8

Published: 16 February 2024| Version 1 | DOI: 10.17632/rng8d63pk3.1
Contributors:
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Description

This repository presents a YOLO annotated dataset of high voltage structures that could potentially cause false alarms in a context related to wildfire detection. The presented dataset, consisting of 1,477 thermal and near-infrared images representing different scenarios, including aerial and ground views, aims to establish a valuable reference for future research in this field based on well-established metric results. Attached to this repository is the dataset created and used during the work. If you wish to use the code sample to replicate our work, please use the link found in the 'Related links' section, which leads directly to the official GitHub of the paper.

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Institutions

Universidad de Las Palmas de Gran Canaria

Categories

Engineering, Deep Learning, Database

Funding

Ministerio de Ciencia e Innovación

PID2020-116569RB-C32

Agencia Canaria de Investigación, Innovación y Sociedad de la Información

TESIS2022010105

Related Links

Software
https://github.com/AntonioIDeTIC/AFAS-YOLOv8
is related to this dataset

Licence