The author explores the efficiency of SVMs in detecting forest fires using challenging datasets, emphasizing the importance of accurate detection systems. The study evaluates SVMs' classification capabilities and their correlation with high-dimensional datasets.
Support Vector Machines (SVMs) exhibit proficiency in forest fire detection through image datasets, aiding in prompt responses and disaster management.