GitHub

Janet33/Latent-Feature-Learning-with-Variational-Autoencoders

In this project we will use the Fashion MNIST computer vision digit dataset and experiment with auto-encoders such as Variational Auto-encoder(VAE) and simple autoencoder. Figure3: A: A sample ...
inc42

What Are Variational Autoencoders? Here’s All You Need to Know

Variational Autoencoders (VAEs) are an artificial neural network architecture to generate new data. They are similar to regular autoencoders, which consist of an encoder and decoder. The encoder takes ...
GitHub

handwritten_digits Project using AutoEncoders (which is a unsupervised learning algorithm.

Deep Autoencoder for Handwritten Digits MNIST This project demonstrates the implementation of a Deep Autoencoder using Keras and TensorFlow to encode and reconstruct handwritten digits from the ...
IEEE

Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing

Abstract: Self-supervised learning through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) image representation learning (IRL), and thus embodies a ...
IEEE

Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications

Abstract: We investigated the adaptation and performance of Masked Autoencoders (MAEs) with Vision Transformer (ViT) architectures for self-supervised representation learning on one-dimensional (1D) ...