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Domain adaptation by mixture of alignments of second- or higher-order scatter tensors

Koniusz, Piotr; Tas, Yusuf; Porikli, Fatih

Description

In this paper, we propose an approach to the domain adaptation, dubbed Second-or Higher-order Transfer of Knowledge (So-HoT), based on the mixture of alignments of second-or higher-order scatter statistics between the source and target domains. The human ability to learn from few labeled samples is a recurring motivation in the literature for domain adaptation. Towards this end, we investigate the supervised target scenario for which few labeled target training samples per category exist....[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Conference paper
URI: http://hdl.handle.net/1885/210115
Source: Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017
Book Title: 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017
DOI: 10.1109/CVPR.2017.755

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