Semantic Segmentation of Jet Fire Temperature Zones using Deep Learning

Wildfires have been on the rise during the past five years. For this reason, the management of wildfires has become critical for the future. This paper shows the comparison between a Deep Learning model and other image processing methods for segmenting infrared images of fire into three zones delimited by temperature. The goal of the test results presented in this paper, and the subsequent tests that will follow it, is to provide insight into the usage of Deep Learning for this new and specific segmentation task. We will ultimately use the knowledge obtained from the tests while building a wildfire detection system that will provide fire engineers with important information for the management of forest fires.