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Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification

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Bibliographic Details
Published in:International Journal of Engineering and Manufacturing
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title International Journal of Engineering and Manufacturing
description
discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
RSS Article
genre Journal Article
id rss_article:12662
institution FRELIP
journal_source_facet International Journal of Engineering and Manufacturing
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
Manufacturing and Technology
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Manufacturing and Technology
Technology & Engineering — Computing
Technology & Engineering
Manufacturing and Technology
Technology & Engineering — Computing
Technology & Engineering
subject_facet Manufacturing and Technology
Technology & Engineering — Computing
Technology & Engineering
title Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
title_auth Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
title_full Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
title_fullStr Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
title_full_unstemmed Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
title_short Enhancing Underwater Object Detection through CNN-based Image Enhancement and Classification
title_sort enhancing underwater object detection through cnn-based image enhancement and classification
topic Manufacturing and Technology
Technology & Engineering — Computing
Technology & Engineering
url https://www.mecs-press.org/ijem/ijem-v16-n2/v16n2-6.html