The application discloses an intelligent
fire point recognition method fusing a physical optimization model and
deep learning, and comprises the following steps: step 1, threshold dynamic
processing is performed according to a physical mechanism model to obtain an optimized adaptive threshold physical mechanism model; step 2, a U-Net
network model is constructed; step 3, a YOLOv5 model is introduced to detect highlighted targets; step 4, the optimized physical mechanism model and the U-Net
network model are used to make a decision to recognize fire points, and
remote sensing fire point preliminary screening results are obtained; and step 5, the highlighted targets recognized by the YOLOv5 model are used as error
elimination on the
remote sensing fire point preliminary screening results, so that the overall precision of the
remote sensing fire point preliminary
screening result recognition is improved; the problems of fire point
false detection and missed detection caused by a fixed threshold are solved, various heat source errors in urban areas that seriously interfere with fire point detection for a long time are eliminated, and the overall precision is further improved; and the problems of poor universality caused by inherent
system errors of traditional single thought algorithms are overcome.