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Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans

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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 Artificial Intelligence
discipline_facet Artificial Intelligence
format Online Article
RSS Article
genre Journal Article
id rss_article:83309
institution FRELIP
journal_source_facet International Journal of Intelligent Systems and Applications
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
Artificial Intelligence
General
Artificial Intelligence
sub_discipline_display General
sub_discipline_facet General
subject_display Artificial Intelligence
General
Artificial Intelligence
Artificial Intelligence
General
Artificial Intelligence
subject_facet Artificial Intelligence
General
Artificial Intelligence
title Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
title_auth Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
title_full Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
title_fullStr Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
title_full_unstemmed Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
title_short Automated Brain Tumor Detection Using Hybrid CNN - Models from T1 – weighted MRI Scans
title_sort automated brain tumor detection using hybrid cnn - models from t1 – weighted mri scans
topic Artificial Intelligence
General
Artificial Intelligence
url https://www.mecs-press.org/ijisa/ijisa-v18-n3/v18n3-6.html