Multi-modal Unsupervised Domain Adaptation for Deformable Registration Based on Maximum Classifier Discrepancy

Christian Kruse; Lasse Hansen; Mattias P. Heinrich‬

doi:10.1007/978-3-658-33198-6_47

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Multi-modal Unsupervised Domain Adaptation for Deformable Registration Based on Maximum Classifier Discrepancy

Christian Kruse Lasse Hansen Mattias P. Heinrich‬

Year: 2021 Informatik aktuell Pages: 192-197 Publisher: Springer Nature

DOI: 10.1007/978-3-658-33198-6_47

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Keywords:

Domain adaptation Artificial intelligence Classifier (UML) Modal Computer science Pattern recognition (psychology) Histogram Image registration Adaptation (eye) Domain (mathematical analysis) Computer vision Machine learning Image (mathematics) Mathematics

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Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

COVID-19 diagnosis using AI

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Multimodal Machine Learning Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Multi-modal Unsupervised Domain Adaptation for Deformable Registration Based on Maximum Classifier Discrepancy

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