An Improved Wildfire Smoke Detection Based on YOLOv8 and UAV Images
An Improved Wildfire Smoke Detection Based on YOLOv8 and UAV Images
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Publisher
Basel: MDPI AG
Journal title
Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Forest fires rank among the costliest and deadliest natural disasters globally. Identifying the smoke generated by forest fires is pivotal in facilitating the prompt suppression of developing fires. Nevertheless, succeeding techniques for detecting forest fire smoke encounter persistent issues, including a slow identification rate, suboptimal accur...
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Full title
An Improved Wildfire Smoke Detection Based on YOLOv8 and UAV Images
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TN_cdi_doaj_primary_oai_doaj_org_article_19c97fd5ea5a4168a2f448fbf4764af7
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_19c97fd5ea5a4168a2f448fbf4764af7
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s23208374
