Implementation of DANN with pytorch

Master's Final Project: Adversarial Domain Adaptation Super Resolution

Third homework of the course "Machine learning and artificial intelligence", focused on deep domain adaptation applied on AlexNet and cross domain validation

Classifying Forged vs Authentic using Domain Adaptation across in new domains in unsupervised settings

Implementation of DANN, a Domain Adaptation algorithm, on the PACS dataset using AlexNet.

Domain Adaptation DL methods adapted for functional MRI (fMRI) data analysis. Enjoy building domain-agnostic models on all levels of data abstraction.

Online Editor for the Dannjs library.

Deep Neural Network predicts pokemon combat outcomes with Dannjs

A two-stage unilateral alignment approach in improving the performance of domain adversarial methods subjected to incomplete target label space while training.

Implementation of Domain adaptation on PACS dataset using a modified version of Alexnet.

Unofficial PyTorch implementation of Domain-Adversarial Training of Neural Networks

Implementation of Domain adaptation on PACS dataset using a modified version of Alexnet.

Omni-supervised domain adversarial training for WM hyperintensity segmentation

python 3 pytorch implementation of DANN

Unsupervised Domain Adaptation for Computer Vision Tasks

Deep Neural Network Library for JavaScript.

This is the repository of Deep Learning for Computer Vision at National Taiwan University.

Provides cuda bindings, kernel maps and device memory managment for Dannjs computations. [Experimental and not complete]