Abstract:
We propose a face classification system based on deep learning algorithm. This system is capable of distinguishing real and fake faces from RGB images taken by a normal c...Show MoreMetadata
Abstract:
We propose a face classification system based on deep learning algorithm. This system is capable of distinguishing real and fake faces from RGB images taken by a normal camera. To do that, we have built a system composed of 4 parts: RGB image processing, HSV image processing, YCrCb image processing, and classification. In order to achieve optimal processing performance, we include encoder and decoder structure models, which eliminate unnecessary components and help the model focus only on the components it gives. Most importantly, this structure helps reduce the complexity of the model. In addition, we have applied a number of special tweaks to the training data. Experimental results indicate that our system gives very good results on the public database.
Published in: 2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
Date of Conference: 14-17 December 2021
Date Added to IEEE Xplore: 03 February 2022
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Conference Location: Tokyo, Japan