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Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection

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Published in:Proceedings of the Nigerian Society of Physical Sciences
Format: Online Article RSS Article
Published: 2026
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container_title Proceedings of the Nigerian Society of Physical Sciences
description
discipline_display African Open Access — Natural Sciences
discipline_facet African Open Access — Natural Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:93489
institution FRELIP
journal_source_facet Proceedings of the Nigerian Society of Physical Sciences
last_indexed 2026-06-20T21:45:54.952Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
African Open Access — Natural Sciences
General
African Open Access — Natural Sciences
sub_discipline_display General
sub_discipline_facet General
subject_display African Open Access — Natural Sciences
General
African Open Access — Natural Sciences
subject_facet African Open Access — Natural Sciences
General
African Open Access — Natural Sciences
title Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
title_alt Modelado de energía cromática espacio-temporal utilizando redes CNN-LSTM mejoradas con atención para la detección de videos deepfake
Modélisation de l'énergie chromatique spatiotemporelle à l'aide de réseaux CNN-LSTM améliorés par attention pour la détection de vidéos deepfake
Modelagem de energia cromática espaço-temporal usando redes CNN-LSTM com atenção aprimorada para detecção de vídeos deepfake
title_auth Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
title_es_txt Modelado de energía cromática espacio-temporal utilizando redes CNN-LSTM mejoradas con atención para la detección de videos deepfake
title_fr_txt Modélisation de l'énergie chromatique spatiotemporelle à l'aide de réseaux CNN-LSTM améliorés par attention pour la détection de vidéos deepfake
title_full Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
title_fullStr Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
title_full_unstemmed Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
title_pt_txt Modelagem de energia cromática espaço-temporal usando redes CNN-LSTM com atenção aprimorada para detecção de vídeos deepfake
title_short Modeling spatiotemporal chromatic energy using attention-enhanced CNN-LSTM networks for deepfake video detection
title_sort modeling spatiotemporal chromatic energy using attention-enhanced cnn-lstm networks for deepfake video detection
topic African Open Access — Natural Sciences
General
African Open Access — Natural Sciences
url https://flayoophl.com/journals/index.php/pnspsc/article/view/270