FrequentNet : A New Deep Learning Baseline for Image Classification
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In this paper, we generalize the idea from the method called "PCANet" to achieve a new baseline deep learning model for image classification. Instead of using principal component vectors as the filter vector in "PCANet", we use basis vectors in discrete Fourier analysis and wavelets analysis as our filter vectors. Both of them achieve comparable performance to "PCANet" in benchmark datasets. It is noticeable that our algorithms do not require any optimization techniques to get those basis.
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