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    <responseDate>2026-10-15T11:51:21Z</responseDate>
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            <header>
                <identifier>oai:data.mendeley.com/jk4r7vcrtd.1</identifier>
                <datestamp>2018-06-02T11:36:57Z</datestamp>
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    <dc:creator>Moon, Hyun Joon</dc:creator>
    <dc:title>Data for: Drone Agriculture Imagery System for Radish Wilt Disease Identification via Efficient Convolutional Neural Network</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>Dataset A contains manually cropped and labeled regions of interest (ROIs) representing three regions: radish, bare ground, and mulching film as shown in Fig. 1. In total, 1,500 ROIs were extracted; 500 ROIs for radish, 500 ROIs for bare ground, and 500 ROIs for mulching film regions
Dataset B contains the  40 images of size (4000x3000) pixel.</dc:description>
    <dc:subject>Computer Vision</dc:subject>
    <dc:subject>Image Processing</dc:subject>
    <dc:subject>Vascular Plants</dc:subject>
    <dc:subject>Deep Learning</dc:subject>
    <dc:contributor>Syed, Ibrahim Hassan</dc:contributor>
    <dc:contributor>Mehmood, Irfan</dc:contributor>
    <dc:contributor>Dang, L. Minh</dc:contributor>
    <dc:contributor>Im, Suhyeon</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/jk4r7vcrtd.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/jk4r7vcrtd.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:date>2018-06-02T11:36:57Z</dc:date>
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