Next day fire prediction via semantic segmentation
<|reference_start|>Next day fire prediction via semantic segmentation: In this paper we present a deep learning pipeline for next day fire prediction. The next day fire prediction task consists in learning models that receive as input the available information for an area up until a certain day, in order to predict the occurrence of fire for the next day. Starting from our previous problem formulation as a binary classification task on instances (daily snapshots of each area) represented by tabular feature vectors, we reformulate the problem as a semantic segmentation task on images; there, each pixel corresponds to a daily snapshot of an area, while its channels represent the formerly tabular training features. We demonstrate that this problem formulation, built within a thorough pipeline achieves state of the art results.<|reference_end|>
@article{alexis2024next,
    title={Next day fire prediction via semantic segmentation},
    author={Konstantinos Alexis, Stella Girtsou, Alexis Apostolakis, Giorgos
  Giannopoulos and Charalampos Kontoes},
    journal={arXiv preprint arXiv:2403.13545},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.13545},
    primaryClass={cs.CV cs.LG}
}