This project was developed in Jupyter Notebook using Python, TensorFlow, and Keras. MNIST dataset: The dataset contains 60,000 training images and 10,000 test images of handwritten digits (0-9). Each ...

This paper proposes an innovative entropy-aware masked autoencoder framework, namely TMAE, for low-cost traffic flow inference. TMAE leverages a small number of selectively measured regions with few ...

This repository contains a comprehensive implementation of Variational Autoencoders (VAEs) applied to two different image datasets: CIFAR-10 and Fashion-MNIST. The project demonstrates how dataset ...

An autoencoder model is employed to predict behavioral patterns and visualize leisure consumption dynamics. Specifically, five key indicators—land diversity, population density, transportation ...

We may receive compensation when you click on links to products we review. Please view our affiliate disclosure. TensorFlow is a popular open-source machine learning framework used to train neural ...