Fine grained vehicle recognition by deep Convolutional Neural Network
Vehicle recognition has been an important topic in intelligent transportation. However, to recognize different vehicle models from a same make is difficult as there are many near identical cars under different brand names. In this paper, we investigated fine grained vehicle recognition via deep Convolutional Neural Network (CNN) Vehicle and the corresponding parts are localized with the help of Region based Convolutional Neural Networks (RCNN) and their features from a set of pre trained CNNs are aggregated to train a SVM classifier. We created a fine grained vehicle dataset and performed subsequent experiments, with preliminary results showing the potentials of the method.
2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP BMEI)