An autoencoder is a type of neural network used to learn efficient codings of input data. This repository implements a simple convolutional autoencoder that takes images as input, compresses them into ...

In this project, I have built an image retrieval system using the AutoEncoder neural network. The network was trained with the CIFAR-10 dataset. The hyperparameters for training the model are provided ...

To ensure a fair comparison with Mostafa’s proposed CAE model, we maintained consistency in data processing, using T1-weighted MRI slice images of the healthy control group for autoencoder ...

Neural networks are used in many tasks today. One of them is the images processing. Autoencoder is very popular neural networks for such problems. Denoising autoencoder is an important autoencoder ...

Electrical capacitance tomography (ECT) image reconstruction has developed decades and made great achievements, but there is still a need to find new theory framework to make image reconstruction ...

Due to the complexity of samples and the limitations in spatial resolution, the spectra in hyperspectral imaging (HSI) are generally contributed to by multiple components, making univariate analysis ...