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    <identifier identifierType="DOI">10.34820/FK2/KQX7BX</identifier>
    <creators><creator><creatorName>Mikogizka Satria Kartika</creatorName><affiliation>(Fakultas Informatika - Data Science)</affiliation></creator></creators>
    <titles>
        <title>Detection of Kids Handwriting For Numbers With Convolutional Neural Network Algorithm</title>
    </titles>
    <publisher>Telkom University Dataverse</publisher>
    <publicationYear>2023</publicationYear>
    <resourceType resourceTypeGeneral="Dataset"/>
    <relatedIdentifiers><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34820/FK2/KQX7BX/AYTOLB</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34820/FK2/KQX7BX/R1V6HZ</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34820/FK2/KQX7BX/ATZ31K</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34820/FK2/KQX7BX/2YCECR</relatedIdentifier></relatedIdentifiers>
    <descriptions>
        <description descriptionType="Abstract">This dataset was used to train and build a model that used to build the Drawing Apps For Kids web app. This dataset was compiled as two-dimensional graphics of the numbers 0 to 9 that were manually written using the Paint program. Each data class's 200 images have a varied resolution, making up a total of 2000 images in the collected datan umum penelitian</description>
    </descriptions>
    <contributors><contributor contributorType="ContactPerson"><contributorName>Nama Lengkap Mikogizka Satria Kartikatanpa gelar</contributorName><affiliation>(Fakultas Informatika - Data Science)</affiliation></contributor></contributors>
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