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To address the problem of unstable training and poor accuracy in image classification algorithms based on generative adversarial networks (GAN), a novel sensor network structure for classification processing using auxiliary classifier generative adversarial networks (ACGAN) is proposed in this paper. Firstly, the real/fake discrimination of sensor samples in the network has been canceled at the output layer of the discriminative network and only the posterior probability estimation of thedoi:10.3390/s19143145 pmid:31319556 pmcid:PMC6679324 fatcat:2cqnoogmx5gl5kgepmxthkd5m4