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Subject Item
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n7:EPrint bibo:AcademicArticle bibo:Article n7:ArticleEPrint
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n4:j.asoc.2018.03.032
dcterms:title
Semi-supervised deep rule-based approach for image classification
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dcterms:date
2018-07-01
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bibo:abstract
In this paper, a semi-supervised learning approach based on a deep rule-based (DRB) classifier is introduced. With its unique prototype-based nature, the semi-supervised DRB (SSDRB) classifier is able to generate human interpretable IF...THEN...rules through the semi-supervised learning process in a self-organising and highly transparent manner. It supports online learning on a sample-by-sample basis or on a chunk-by-chunk basis. It is also able to perform classification on out-of-sample images. Moreover, the SSDRB classifier can learn new classes from unlabelled images in an active way becoming dynamically self-evolving. Numerical examples based on large-scale benchmark image sets demonstrate the strong performance of the proposed SSDRB classifier as well as its distinctive features compared with the “state-of-the-art” approaches.
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bibo:volume
68