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Unsupervised Evaluation of Lidar Domain Adaptation

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020
In this work, we investigate the potential of latent representations generated by Variational Autoencoders (VAE) to analyze and distinguish between real and synthetic data. Although the details of the domain adaptation task are not the focus of this work, we use the example of simulated lidar data adapted by a generative model to match real lidar data.
Hubschneider, Christian   +2 more
openaire   +2 more sources

Assisted Unsupervised Domain Adaptation

2023 IEEE International Symposium on Information Theory (ISIT), 2023
Cheng Chen   +3 more
openaire   +1 more source

Adversarially robust unsupervised domain adaptation

Artificial Intelligence
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lianghe Shi, Weiwei Liu
openaire   +2 more sources

A simple approach for unsupervised domain adaptation

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
Domain adaptation (DA) aims to eliminate the difference between the distribution of labeled source domain on which a classifier is trained and that of unlabeled or partly labeled target domain to which the classifier is to be applied. Compared with the semi-supervised domain adaptation where some labeled data from target domain is utilized to help ...
Xifeng Guo 0001, Wei Chen, Jianping Yin
openaire   +2 more sources

Distributionally robust unsupervised domain adaptation

Journal of Computational and Applied Mathematics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yibin Wang 0003, Haifeng Wang
openaire   +2 more sources

Adaptive Feature Swapping for Unsupervised Domain Adaptation

Proceedings of the 31st ACM International Conference on Multimedia, 2023
Junbao Zhuo   +4 more
openaire   +1 more source

Pseudo Labels for Unsupervised Domain Adaptation: A Review

Electronics (Switzerland), 2023
Yundong Li, Longxia Guo
exaly  

Unsupervised variational domain adaptation

Machine Learning
Yundong Li   +3 more
openaire   +1 more source

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