Some mini-projects using well known datasets to practice important deep learning concepts.
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Updated
Apr 2, 2024 - Python
Some mini-projects using well known datasets to practice important deep learning concepts.
This repository contains notebooks with academic projects to practice and explore image creation using AI, where the use of VAE (Variational Autoencoders) and GANs (Generative Adversarial Networks) was explored to generate human faces based on a dataset with examples.
Deep Convolutional Generative Adversarial Network (DCGAN) implementation using PyTorch trained on the MNIST dataset to generate images of handwritten digits
Solutions for Advanced Image Analysis course assignments, featuring model designs for image summation and generation with MNIST, and style transfer using CycleGAN with MNIST and SVHN datasets.
This repo implements a simple GAN with fc layers and trains it on MNIST
Generative models (GAN, VAE, Diffusion Models, Autoregressive Models) implemented with Pytorch, Pytorch_lightning and hydra.
Simple Implementation of many GAN models with PyTorch.
DCGAN Fashion MNIST generator
A collection of different latent variable and generative models
A PyTorch implementation for StyleGAN with full features.
Code for my experiments on AOT-GAN.
Virtual Fashion TryON - Fashion(Garment) transfer on a given target using Deep learning.
A PyTorch implementation using CycleGAN architecture, to read in an image from a set X and transform it so that it looks as if it belongs in set Y .
Deep Learning Projects using Python & Pytorch
GAN related
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