Detection of Animals and humans in forest fires using Yolov8
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Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
- The study uses the YOLOv8 deep learning algorithm to detect fire, smoke, humans, and animals in outdoor images. The importance of forests in protecting the biosphere is emphasized, and forest fires are identified as a major risk to the environment and living beings. The researchers created a custom dataset of outdoor images and manually annotated them. The YOLOv8 model was trained on this dataset, and its overall performance was evaluated, with varying results for different object classes. The study identified areas for improvement in the model's ability to detect small instances of fire and smoke and differentiate between animals and humans. The impact of image quality on the model's performance was also highlighted. Overall, the study provides a comprehensive evaluation of YOLOv8's performance in detecting outdoor objects and identifies areas for improvement.
Açıklama
Anahtar Kelimeler
Forest fires, YOLOv8, Deep learning algorithm, Object detection, Performance evaluation
Kaynak
Journal of Electrical Systems
WoS Q Değeri
Scopus Q Değeri
Cilt
20
Sayı
9
Künye
Alsamurai, M. Q. F., Çevik, M. (2024). Detection of Animals and humans in forest fires using Yolov8. Journal of Electrical Systems, 20(9-SI), 831-843.
