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contributor authorLilian Tais de Gouveia
contributor authorLuciano da Fontoura Costa
contributor authorLuciano José Senger
contributor authorMarcelo Keese Albertini
contributor authorRodrigo Fernandes de Mello
date accessioned2017-05-08T21:40:19Z
date available2017-05-08T21:40:19Z
date copyrightJanuary 2011
date issued2011
identifier other%28asce%29cp%2E1943-5487%2E0000078.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/59038
description abstractThis paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.
publisherAmerican Society of Civil Engineers
titleEntropy-Based Approach to Analyze and Classify Mineral Aggregates
typeJournal Paper
journal volume25
journal issue1
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/(ASCE)CP.1943-5487.0000071
treeJournal of Computing in Civil Engineering:;2011:;Volume ( 025 ):;issue: 001
contenttypeFulltext


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