Fig. 1

Conceptual framework of the shallow networks investigated in this work. First, the input image is pre-processed by mean-removal or z-normalization. Then, the normalized image is processed by convolutional layers obtained by the reshaping of PCA or LDA basis vectors. The convolutional layers are obtained from either unsupervised or supervised approach. After that, a feature mapping strategy is applied, which consists of binarization and block-wise histogramming. Finally, classification is performed by KNN or SVM