FIRE-BYOL: A Real-Time Grassland Active-Fire Detection Algorithm Fusing VIIRS Fire Products and Himawari-8/9 Data
This study proposes FIRE-BYOL, an active-fire detection framework integrating BYOL self-supervised learning with supervised fine-tuning that offers a highly effective, data-efficient technical solution for high-frequency regional fire monitoring on the Mongolian Plateau and similar environments.