Generate Random Faces which do not exists. I trained a Deep Convolution GAN (DCGAN) on 100k celebrities photos.
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Updated
Oct 15, 2019 - Python
Generate Random Faces which do not exists. I trained a Deep Convolution GAN (DCGAN) on 100k celebrities photos.
Python3 implementation of the Unsupervised Deep Learning Algorithm, Restricted Boltzmann Machine.
Python implementation of the unsupervised Deep Learning Algorithm SOM
An easy way to use the released TransCoder by Facebook AI Research to convert code from one programming language to another using unsupervised neural machine translation (NMT) systems that use deep-learning to translate text from one natural language to another and is trained only on monolingual source data.
Unsupervised Style Transfer, transferring sentiment of reviews using classification attention weights.
This repository provides implementation simplified Variational Autoencoder (VAE), producing smooth latent space completely unsupervised manner. And this can be used as generative model as well.
A pytorch implementation of: "Unsupervised Deep Learning for Structured Shape Matching"
Unsupervised image segmentation based on depth and normal maps clustering.
In this repo, all about Deep Learning and I covered both Supervised and Unsupervised Learning Techniques with Practical Implementation. Everything from scratch and I solved a lot of different problems with different Neural Network Architectures.
Codes for the paper "Deep sparse and low-rank for HSI denoising" in Proceeding of IGARSS 2022, Kuala Lumpur.
Codes for the paper "Hyperspectral super-resolution by unsupervised convolutional neural network and SURE" in Proceeding of IGARSS 2022, Kuala Lumpur, Malaysia.
🔥GrowSP in PyTorch (CVPR 2023)
Simulation code for "Unsupervised Deep Learning for Massive MIMO Hybrid Beamforming" by Hamed Hojatian, Jeremy Nadal, Jean-Francois Frigon, Francois Leduc-Primeau, 2020.
Basic to advanced level of generative model with code.
Transformer-based Models for Unsupervised Anomaly Segmentation in Brain MR Images
Unsupervised Deep Learning-based Pansharpening with Jointly-Enhanced Spectral and Spatial Fidelity
Pansharpening by convolutional neural networks in the full resolution framework
[MICCAI 2024] CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation
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