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                <identifier>oai:data.mendeley.com/mnbrrzdzgs.1</identifier>
                <datestamp>2025-09-15T14:47:15Z</datestamp>
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    <dc:creator id="https://orcid.org/0009-0005-4761-9809">Pranta, Gourab Kumar</dc:creator>
    <dc:title>A collection of 3,318 high-resolution lychee leaf images captured under natural lighting conditions with a consistent background for optimal clarity.</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>Dedicated Dataset: A collection of 3,318 high-resolution lychee leaf images captured under natural lighting conditions with a consistent background for optimal clarity.
Four Disease Classes:
    Healthy Leaf: 1,032 images
    Erinose Mite: 1,049 images
    Fungal Disease: 726 images
    Insect Infected: 511 images     
Purpose: 
    1. Supports machine learning and computer vision applications for agricultural disease detection.
    2. Facilitates early identification and classification of eggplant diseases. 
    3. Enables the design of smart farming systems to track crop health, reduce reliance on pesticides, and foster eco-friendly cultivation methods.</dc:description>
    <dc:subject>Disease</dc:subject>
    <dc:subject>Leaf Area</dc:subject>
    <dc:subject>Lychee</dc:subject>
    <dc:subject>Meta Dataset</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/mnbrrzdzgs.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/mnbrrzdzgs.1</dc:identifier>
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    <dc:date>2025-09-15T14:47:15Z</dc:date>
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