Fire image detection and classification analysis based on VGG16 image processing model

Abstract

Fire image classification technology refers to the classification and recognition of fire images through computer vision technology in order to take timely countermeasures. With the development of computer vision technology, fire image classification technology has been widely studied and applied. Deep learning techniques have achieved great success in the field of image classification, with researchers classifying and identifying fire images by using deep learning models such as convolutional neural networks. This paper introduces the research background and application of fire image classification technology, and the experimental results of detection and classification analysis of fire image based on vgg16 image processing model. The model can classify and identify fire images well and achieve good prediction effect. The accuracy of training set and test set is stable at 99%, the accuracy and accuracy of the model reach 98%, and the recall rate and F1 score reach 99%. The application of fire image classification technology is of great significance. By using computer vision technology to classify and identify fire images, it can improve the accuracy and efficiency of fire monitoring and early warning system, timely detect and control fire, and reduce the loss caused by fire. At the same time, the continuous development of deep learning technology also provides a broader space for the research and application of fire image classification technology.