Improving generative adversarial network for binary classification on similar and imbalance data

Improving generative adversarial network for binary classification on similar and imbalance data

碩士 === 國立中央大學 === 資訊工程學系 === 107 === 　　We propose a semi-supervised convolutional neural network for binary classification, which combines variational autoencoder with generative adversarial network (GAN) to classify similar objects by thresholding the similarities between original images and genera...

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Bibliographic Details
Main Authors:	Yih-Shyang Chiu, 邱義翔
Other Authors:	Din-Chang Tseng
Format:	Others
Language:	zh-TW
Published:	2019
Online Access:	http://ndltd.ncl.edu.tw/handle/24s6hz

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