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An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification

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Bibliographic Details
Published in:Journal of Natural Science, Biology and Medicine
Format: Online Article RSS Article
Published: 2021
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container_title Journal of Natural Science, Biology and Medicine
description
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genre Journal Article
id rss_article:82182
institution FRELIP
journal_source_facet Journal of Natural Science, Biology and Medicine
publishDate 2021
publishDateSort 2021
record_format rss_article
spellingShingle An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
Biology
General
Biology
sub_discipline_display General
sub_discipline_facet General
subject_display Biology
General
Biology
Biology
General
Biology
subject_facet Biology
General
Biology
title An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
title_auth An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
title_full An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
title_fullStr An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
title_full_unstemmed An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
title_short An Empirical Development of Hyper-Tuned CNN Using Spotted Hyena Optimizer For Bio-Medical Image Classification
title_sort an empirical development of hyper-tuned cnn using spotted hyena optimizer for bio-medical image classification
topic Biology
General
Biology
url https://jnsbm.org/an-empirical-development-of-hyper-tuned-cnn-using-spotted-hyena-optimizer-for-bio-medical-image-classification