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PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases

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Published in:IEEE Access
Format: Online Article RSS Article
Published: 2026
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spellingShingle PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Computer Science & Information Science
Computer Science & IT
Engineering & Technology
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
subject_facet Computer Science & Information Science
Computer Science & IT
Engineering & Technology
title PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
title_auth PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
title_full PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
title_fullStr PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
title_full_unstemmed PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
title_short PalmRachis-BiLSTM-Attn: An Anatomically Guided Explainable Deep Learning Framework for Spatial–Temporal Progression Modeling of Date-Palm Leaf Diseases
title_sort palmrachis-bilstm-attn: an anatomically guided explainable deep learning framework for spatial–temporal progression modeling of date-palm leaf diseases
topic Computer Science & Information Science
Computer Science & IT
Engineering & Technology
url http://ieeexplore.ieee.org/document/11417755