This study aims to explore an autoencoder-based method for generating brain MRI images of patients with Autism Spectrum Disorder (ASD) and non-ASD individuals, and to discriminate ASD based on the ...
The primary objective of this project is to develop an efficient model for data compression. The focus is on leveraging complex autoencoder architectures to achieve significant dimensionality ...
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning). The encoding is validated and refined by attempting to regenerate the ...
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