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A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features

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Published in:Cybernetics and Information Technologies
Format: Online Article RSS Article
Published: 2025
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container_title Cybernetics and Information Technologies
description
discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
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genre Journal Article
id rss_article:25801
institution FRELIP
journal_source_facet Cybernetics and Information Technologies
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
Internet
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Internet
Technology & Engineering — Computing
Technology & Engineering
Internet
Technology & Engineering — Computing
Technology & Engineering
subject_facet Internet
Technology & Engineering — Computing
Technology & Engineering
title A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
title_auth A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
title_full A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
title_fullStr A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
title_full_unstemmed A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
title_short A Novel Hybrid Deep Learning Framework for Image Captioning Using Combined Semantic and Object-Level Features
title_sort a novel hybrid deep learning framework for image captioning using combined semantic and object-level features
topic Internet
Technology & Engineering — Computing
Technology & Engineering
url https://sciendo.com/article/10.2478/cait-2025-0036