FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised Learning

Benchmark Model Rank Results
remote-sensing-image-classification-on-fireriskResNet-50#1Accuracy (%): 63.20
remote-sensing-image-classification-on-fireriskViT-B/16#2Accuracy (%): 63.31
remote-sensing-image-classification-on-fireriskDINO (ViT-B/16)#3Accuracy (%): 63.36
remote-sensing-image-classification-on-fireriskMAE (ViT-B/16)#4Accuracy (%): 65.29