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An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model

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Bibliographic Details
Published in:Biophysics Reports
Format: Online Article RSS Article
Published: 2019
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container_title Biophysics Reports
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
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genre Journal Article
id rss_article:18055
institution FRELIP
journal_source_facet Biophysics Reports
publishDate 2019
publishDateSort 2019
record_format rss_article
spellingShingle An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
Biophysics
Natural Sciences — Physical Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Physical Sciences
sub_discipline_facet Natural Sciences — Physical Sciences
subject_display Biophysics
Natural Sciences — Physical Sciences
Natural Sciences
Biophysics
Natural Sciences — Physical Sciences
Natural Sciences
subject_facet Biophysics
Natural Sciences — Physical Sciences
Natural Sciences
title An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
title_auth An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
title_full An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
title_fullStr An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
title_full_unstemmed An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
title_short An Automatic Threshold Segmentation and Mining Optimum Credential Features by Using HSV Model
title_sort an automatic threshold segmentation and mining optimum credential features by using hsv model
topic Biophysics
Natural Sciences — Physical Sciences
Natural Sciences
url https://link.springer.com/article/10.1007/s13319-019-0229-8