Udacity Machine Learning Nano Degrees Project
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Updated
Aug 16, 2020 - HTML
Udacity Machine Learning Nano Degrees Project
Official Implementation of NVC: Robust Unsupervised Domain Adaptation through Negative-View Regularization
TF 2.x implementation of UDA (Unsupervised Data Augmentation for Consistency Training, 2019).
[IEEE TMI 2022] Official Implementation for "LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation"
This repo contains a simple and clear PyTorch implementation of the main building blocks of "Unsupervised Data Augmentation for Consistency Training" by Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong, Quoc V. Le
[MICCAI 2022] Official Implementation for "Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation"
[CVPRW 2021] Rethinking Ensemble-Distillation for Semantic Segmentation Based Unsupervised Domain Adaptation
A minimal PyTorch implementation of YOLOv3, with support for training, inference and evaluation. An addtional implementation of two Unsupervised Domain Adaptation methods (Direct Entropy Minimization and Fourier Domain Adaptation) integrated in the architecture.
This repository holds a small framework to evaluate unsupervised domain adaptation methods in combination with a CenterNet object detection network.
[MICCAI 2021] Official Implementation for "MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels"
(NeurIPS2019) Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
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