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            <header>
                <identifier>oai:data.mendeley.com/gtmz34sjvc.1</identifier>
                <datestamp>2026-09-17T13:19:16Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>Ayet, Jobaet Hasan</dc:creator>
    <dc:title>GuavaLeafBD: A Labeled Image Dataset of Guava Leaf Diseases for image based classification</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This dataset supports research in plant pathology and computer vision by providing a labeled image collection of guava leaf diseases and healthy leaves collected from guava gardens in the Chittagong Division of Bangladesh. The dataset contains 524 images representing five categories: Red Rust, Yellow Spot, Healthy, Caterpillar, and Die Back.

The guava leaf images were collected from guava gardens in Kanchannagar , Chandanaish, Chittagong, Bangladesh, an area well known for guava cultivation. The images were captured using two high-end smartphones, Samsung Galaxy S25 Ultra and iPhone 15 Pro Max.

The dataset contains the following class distribution:

• Red Rust: 73 images
• Yellow Spot: 106 images
• Healthy: 101 images
• Caterpillar: 207 images
• Die Back: 37 images</dc:description>
    <dc:subject>Computer Vision</dc:subject>
    <dc:subject>Convolutional Neural Network</dc:subject>
    <dc:subject>Deep Learning</dc:subject>
    <dc:subject>Explainable Artificial Intelligence</dc:subject>
    <dc:subject>Agriculture</dc:subject>
    <dc:contributor>Mostafa, Golam </dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/gtmz34sjvc.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/gtmz34sjvc.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:date>2026-09-17T13:19:16Z</dc:date>
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