My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN (Goodfellow et al.), cGAN (Mirza et al.), DCGAN (Radford et al.), etc.
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Updated
Dec 7, 2020 - Python
My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN (Goodfellow et al.), cGAN (Mirza et al.), DCGAN (Radford et al.), etc.
Train a DCGAN model on Colaboratory to generate Steam banners.
Generation of Human-Like handwritten digits using different GAN Architectures. The models were developed using Low-Level Tensorflow.
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…
Generation of images from NORB dataset using DC-GAN
Implementations of GANs in PyTorch for Pokemon image generation
A very simple and plain DC GAN to generate Image Flower Pictures out of the dataset.
Deep Learning model that generates Pokemon images
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!
Generating fake images using DC-GANs
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