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Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals

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Published in:IET Computer Vision
Format: Online Article RSS Article
Published: 2026
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container_title IET Computer Vision
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discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
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institution FRELIP
journal_source_facet IET Computer Vision
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
subject_facet Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
title Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
title_auth Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
title_full Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
title_fullStr Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
title_full_unstemmed Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
title_short Predicting Fire Heat Release Rate Using Deep Perceptual and Detail‐Aware Hybrid Feature Fusion From Early Smoke Signals
title_sort predicting fire heat release rate using deep perceptual and detail‐aware hybrid feature fusion from early smoke signals
topic Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
url https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cvi2.70054?af=R