Car Damage Detection Analysis using Deep Learning, Computer Vision Techniques

Car damage detection is an important field of research due to its potential application in accident prevention, insurance claims, and law enforcement.In this paper, we propose a deep learning approach for car damage detection using image analysis.We use a pre-trained convolutional neural network (CNN) model to extract features from the input images and then train a support vector machine (SVM) classifier on the extracted features.The proposed approach is evaluated on a publicly available dataset of car damage images and achieves a high accuracy of 94% in car damage detection.Our results demonstrate the effectiveness of deep learning in car damage detection and have potential for real-world applications..