About: Semi-supervised deep rule-based approach for image classification

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An Entity of Type : bibo:AcademicArticle, within Data Space : linkeddata.uriburner.com:28898 associated with source document(s)

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #90203 Semi-supervised deep rule-based approach for image classification
sameAs	Semi-supervised deep rule-based approach for image classification
Title	Semi-supervised deep rule-based approach for image classification
described by	https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2018-07-01
Creator	Plamen P. Angelov Xiaowei Gu
status	peer reviewed published
Publisher	Elsevier
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.
Is Part Of	Applied Soft Computing https://kar.kent.ac.uk/id/repository
Subject	QA 75 Electronic computers. Computer science
list of authors	https://kar.kent.ac.uk/id/eprint/90203#authors
volume	68
is topic of	https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #90203 Semi-supervised deep rule-based approach for image classification

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