Artificial Intelligence
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Updated
May 12, 2024 - Jupyter Notebook
Artificial Intelligence
We implement a conditional Deep Convolutional Generative Adversarial Network (DCGAN) sampling high-quality Street View House Numbers (SVHN), conditioned on an embedding of a desired label.
A PhotoReaslistic AI GAN model to generate photorealistic faces on a large scale
A template repository for GANs
Generating Realistic Human Faces with Generative Networks
Generative Adversarial Network for Nintendo Entertainment System Music.
Tasks for Architecture of Neural Networks Course @ ITMO University
Deep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.
Implementation of basic DCGAN (deep convolutional generative adversarial network), inspired heavily from Jason Brownlee's post on machinelearningmastery.com.
In This Repo I've Built DC-GAN as a part of Gan Series I'm Building
A Conditional Deep Convolutional Generative Adversarial Network implemented in PyTorch, trained on the Fashion MNIST dataset.
Code for our paper "Generative Adversarial Network with Soft-Dynamic Time Warping and Parallel Reconstruction for Energy Time Series Anomaly Detection" and its extension.
This is a course project for the Artificial Neural Network course at NTNU. In this project, I built a DCGAN model to generate anime images.
Repo of all deep learning models
Project code that has been developed during the Udacity Deep Learning Nano Degree.
Creating Anime Faces using Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN, StyleGAN, StyleGAN2 and StyleGAN3. Top repos on GitHub for AnimeFace GAN Generative AI Models
Using DCGANs to generate anime faces.
Face generation with deep convolutional generative adversarial network using PyTorch and Jupyter Notebook.
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