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USING SEMI-SUPERVISED VARIATIONAL AUTOENCODER FOR WI-FI-BASED INDOOR LOCALIZATION
USING SEMI-SUPERVISED VARIATIONAL AUTOENCODER FOR WI-FI-BASED INDOOR LOCALIZATION
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机译:使用半监控变形Autiachoder进行基于Wi-Fi的室内定位
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摘要
Methods of training predictors for the location of a computing device in an indoor environment are provided. The methods comprise receiving training data comprising labelled data and unlabelled data. A method of training a predictor comprises training a variational autoencoder, wherein the variational autoencoder comprises encoder neural networks, which encode signal strength values in a latent variable, and decoder neural networks, which decode the latent variable to reconstructed signal strength values, and training a classification neural network that employs the latent variable to generate a predicted location. Another method of training a predictor comprises training a classification neural network together with a variational autoencoder, wherein the classification neural network receives signal strength values of the training data as input and outputs a predicted location to decoder neural networks of the variational autoencoder.
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