Search Results for: Generative Adversarial Networks

Table of Contents Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) Preface Enhanced Super-Resolution GANs Configuring Your Development Environment Having Problems Configuring Your Development Environment? Project Structure Configuring the Prerequisites Implementing Data Processing Utilities Implementing the ESRGAN Architecture Building the Training Pipeline…

Table of Contents Super-Resolution Generative Adversarial Networks (SRGAN) A Brief Recap of GANs Super-Resolution Using GANs Configuring Your Development Environment Having Problems Configuring Your Development Environment? Project Structure Creating the Configuration Pipeline Building the Data Processing Pipeline Implementing the SRGAN…

This post covers the intuition of Generative Adversarial Networks (GANs) at a high level, the various GAN variants, and applications for solving real-world problems. This is the first post of a GAN tutorial series: Intro to Generative Adversarial Networks (GANs)…

In this tutorial, you will learn how to break deep learning models using image-based adversarial attacks. We will implement our adversarial attacks using the Keras and TensorFlow deep learning libraries. Imagine it’s twenty years from now. Nearly all cars and…

Table of Contents Exploring GAN Code Generation with Gemini Pro and ChatGPT-3.5: A Comparative Study Introduction to GAN Development with Gemini Pro Expectations from the Generated Code Understanding Generative Adversarial Networks Configuring Gemini Pro for PyTorch GAN Code Creation and…

Table of Contents Exploring the Landscape of Machine Learning: Techniques, Applications, and Insights Introduction: The Power of Machine Learning in Modern Industries What Is Machine Learning? Understanding the Core Types of Machine Learning Techniques Supervised Learning: From Basics to Real-World…

Table of Contents Generating Faces Using Variational Autoencoders with PyTorch Configuring Your Development Environment Need Help Configuring Your Development Environment? Project Structure About the Dataset Overview Class Distribution Data Preprocessing Data Split Configuring the Prerequisites Defining the Data Utilities Defining…

Table of Contents A Deep Dive into Variational Autoencoder with PyTorch Introduction Comparison with Convolutional Autoencoder Architecture Latent Space Loss Function Why Does VAE Stand Out? Why Does the Encoder of a VAE Follow a Gaussian Distribution? Objective Functions of…

Table of Contents Introduction to Autoencoders What Are Autoencoders? How Autoencoders Achieve High-Quality Reconstructions? Revisiting the Story Types of Autoencoder Vanilla Autoencoder Convolutional Autoencoder (CAE) Denoising Autoencoder Sparse Autoencoder Variational Autoencoder (VAE) Sequence-to-Sequence Autoencoder What Are the Applications of Autoencoders?…