Analysis of Deep Learning Architectures and Efficacy of Detecting Forest Fires

2022/12/08 by Ryan Marinelli, Marinelli, Ryan
Engineering · Environmental Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Fire Detection and Safety Systems #Fire effects on ecosystems #Landslides and related hazards

paper · pdf · doi:10.48550/arxiv.2212.04030

openalex publication_date 2022/12/08 · openalex created_date 2022/12/22 · openalex updated_date 2026/07/28

Abstract

The aim of this research is to review the state of computer vision as applied to combatting forest fires. My motivation to research this topic comes from the urgency with which new participants and stakeholders require guidance in this field. One of these new stakeholder groups are practitioners of machine learning that lack domain expertise. Introducing these new entrants to domain specific datasets and methods is critical to supporting this aim as general computer vision datasets are insufficient to support specialized research initiatives. The overarching aim of the research is to introduce datasets and methods to make them more accessible to the community.

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