This repository demonstrates a simple autoencoder model for compressing and reconstructing images. The autoencoder is built using TensorFlow and Keras and is trained on a dataset of images to learn a ...

Each image is 28 by 28 = 784 pixels ... 1.0] to match the input values. Many of the autoencoder examples I see online use relu() activation for interior layers. The relu() function was designed for ...

Abstract: In this paper, we treat the image generation task using an autoencoder, a representative latent model. Unlike many studies regularizing the latent variable’s distribution by assuming a ...

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 autoencoder managed to reduce the dimensions of the images to 15x15, which represents a used storage space of only 22% of the original space occupied by each original image. After the compression, ...

Each image is 28 by 28 = 784 pixels ... 1.0] to match the input values. Many of the autoencoder examples I see online use relu() activation for interior layers. The relu() function was designed for ...