YOlOv5s-ACE: Forest Fire Object Detection Algorithm Based on Improved YOLOv5s
Work
Year: 2024
Type: article
Source: Fire Technology
Cites: 41
Cited by: 4
Related to: 10
FWCI: 2.622
Citation percentile (by year/subfield): 79.14
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Sustainable Development Goal Climate action
Open Access status: closed
Funders National Natural Science Foundation of China, National Natural Science Foundation of China, Foundation of Liaoning Province Education Administration, Liaoning Revitalization Talents Program
Grant IDS 61572082, 61976027, JYTZD2023175, XLYC2008002