Research on vehicle apparent damage assessment technology based on intelligent regression calculation

Abstract Aiming at the requirements of effective assessment and accurate quantification of vehicle target apparent damage degree in war, natural disasters and other environments, this paper presents a damage assessment technique based on deep learning regression calculation. First, the image containing vehicle target is preprocessed by scale adjustment, segmentation and graying. Then, extracting and fusing the high-dimensional features of the preprocessed image through the deep convolution neural network. At last, obtaining the evaluation value of vehicle target damage degree through the fusion feature calculation of full connection regression network. In this paper, the automobile target is taken as the experimental object, and completing the relevant data collection, training and testing. The experimental results show the accuracy and effectiveness of this method for vehicle target apparent damage degree evaluation.