The invention relates to the field of
image detection, and especially relates to an automobile surface damage classification method and device based on
deep learning. According to the method and the device, the classification method and device are provided for the problems in the prior art. Characteristic learning and classification are carried out on input to-be-detected images. Specifically, candidate areas are extracted from the to-be-detected images to by employing an area selective
search algorithm, and location information of the candidate areas are recorded; the to-be-detected images are input into a characteristic diagram extraction
network model without an output layer, thereby extracting the characteristic vectors of the candidate areas of the to-be-detected images; the characteristic vectors of the candidate areas are input into an
SVM classifier to find target characteristic vectors; the locations of the corresponding candidate areas on the to-be-detected images, namely, the target areas of the to-be-detected images, are found according to the locations of the target characteristic vectors in the characteristic diagram; and the target areas of the to-be-detected images are input into an optimum classification
network model, and the probabilities of the areas on damage levels are output.