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SCIENCE CHINA Information Sciences, https://doi.org/10.1007/s11432-018-9862-9

FrFT convolutional face: towards robust face recognition using fractional Fourier transform and convolutional neural networks

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Abstract

In this paper, we propose to jointly use FrFT and CNN in a cascaded fashion, called FrFT convolutional face, which is capable of deeply extracting the richer facial features from both spatial domain and fractional Fourier domain. With the varied combination of different orders in FrFT and different components (e.g., amplitude and phase information), the proposed FrFT convolutional face is expected to learn the facial variations more effectively.


Funded by

This research was supported, in part, by the National Natural Science Foundation of China under Grant 61331021 and Grant 61421001, and, in part, by the National Natural Science Foundation of China (U1833203).

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