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An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments

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Bibliographic Details
Published in:International Journal of Intelligent Systems and Applications
Format: Online Article RSS Article
Published: 2026
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container_title International Journal of Intelligent Systems and Applications
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:42997
institution FRELIP
journal_source_facet International Journal of Intelligent Systems and Applications
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
— — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display — — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
— — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
subject_facet — — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
title An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
title_auth An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
title_full An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
title_fullStr An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
title_full_unstemmed An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
title_short An Optimized Deep Neural Network Model for Image Classification in Resource-constrained Environments
title_sort an optimized deep neural network model for image classification in resource-constrained environments
topic — — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
url https://www.mecs-press.org/ijisa/ijisa-v18-n2/v18n2-5.html