dc-gan

Here are 14 public repositories matching this topic...

gordicaleksa / pytorch-GANs

My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN (Goodfellow et al.), cGAN (Mirza et al.), DCGAN (Radford et al.), etc.

python machine-learning deep-learning pytorch gans generative-adversarial-networks deep-learning-tutorial conditional-gan dc-gan vanilla-gan gan-tutorial generative-adversarial-nets

Updated Dec 7, 2020
Python

woctezuma / google-colab

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Train a DCGAN model on Colaboratory to generate Steam banners.

steam steam-games generative-adversarial-network gan steam-api dcgan colab steam-pics steam-data dcgan-model dc-gan colaboratory google-colab colab-notebook steam-store steam-game google-colaboratory google-colab-notebook steam-gan

Updated May 29, 2021
Jupyter Notebook

kochlisGit / Generative-Adversarial-Networks

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Generation of Human-Like handwritten digits using different GAN Architectures. The models were developed using Low-Level Tensorflow.

python computer-vision tensorflow keras discriminator generative-adversarial-network handwritten-digits gans low-level-programming info-gan wgan-gp dc-gan stylegan ac-gan stylegan2 discriminator-model gan-architectures gan-improvements

Updated Feb 15, 2022
Python

shashanktyagi / DC-GAN-on-NORB-dataset

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Generation of images from NORB dataset using DC-GAN

deep-learning generative-adversarial-network norb dc-gan

Updated Jul 29, 2017
Python

Implemented Vanilla RNN and LSTM networks, combined these with pretrained VGG-16 on ImageNet to build image captioning models on Microsoft COCO dataset. Explored use of image gradients for generating new images and techniques used are Saliency Maps, Fooling Images and Class Visualization. Implemented image Style Transfer technique from 'Image St…

numpy pytorch lstm gan style-transfer rnn mnist-dataset saliency-map dc-gan cs231n-assignment fooling-images class-visualization coco-dataset ls-gan microsoft-coco

Updated Aug 31, 2018
Jupyter Notebook

Karthi-DStech / GAN-Driven-Biomaterial-Discovery

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This repository encompasses a comprehensive research of Generative Adversarial Networks (GANs) for Biomaterial Discovery. Our research delves into the generation of intricate biomaterial topographies through the innovative application of AI/ML techniques. Discover our findings, code implementations and datasets in this repository!

wgan wgan-gp conditional-gan dc-gan vanilla-gan auxiliary-classifier-gan