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Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans

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Published in:VFAST Transactions on Software Engineering
Format: Online Article RSS Article
Published: 2026
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container_title VFAST Transactions on Software Engineering
description
discipline_display Software
discipline_facet Software
format Online Article
RSS Article
genre Journal Article
id rss_article:99156
institution FRELIP
journal_source_facet VFAST Transactions on Software Engineering
last_indexed 2026-07-04T03:35:03.975Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
Software
General
Software
sub_discipline_display General
sub_discipline_facet General
subject_display Software
General
Software
subject_facet Software
General
Software
title Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
title_alt Aprendizaje profundo híbrido para la detección de tumores cerebrales mediante exploraciones multimodales
Apprentissage profond hybride pour la détection des tumeurs cérébrales à l'aide de scans multi-modaux
Aprendizado Profundo Híbrido para Detecção de Tumores Cerebrais Usando Imagens Multimodais
title_auth Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
title_es_txt Aprendizaje profundo híbrido para la detección de tumores cerebrales mediante exploraciones multimodales
title_fr_txt Apprentissage profond hybride pour la détection des tumeurs cérébrales à l'aide de scans multi-modaux
title_full Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
title_fullStr Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
title_full_unstemmed Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
title_pt_txt Aprendizado Profundo Híbrido para Detecção de Tumores Cerebrais Usando Imagens Multimodais
title_short Hybrid Deep Learning for Brain Tumor Detection Using Multi-Modal Scans
title_sort hybrid deep learning for brain tumor detection using multi-modal scans
topic Software
General
Software
url https://vfast.org/journals/index.php/VTSE/article/view/2423