The problem addressed in this paper is feature extraction and classification of images. As a solution, we proposed a Deep Wavelet Network architecture based on the Wavelet Network and the Stacked Auto-encoders. In this work, we shifted from the deep learning based on neural networks to deep learning based on wavelet networks. The latter doesn’t change the general form of the Deep Learning based on the Neural Network but it is a novel method that shows the process of feature extraction and explains the system of image classification. Our Deep Wavelet Network is created for the training and the classification phase. After the training phase, a linear classifier is applied. Finally, the experimental test of our method is in the COIL-100 dataset.
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