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          <identifier identifierType="DOI">10.5522/04/14993589.v1</identifier>
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              <creatorName>Wang, Seunghyeon</creatorName>
              <givenName>Seunghyeon</givenName>
              <familyName>Wang</familyName>
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            <creator>
              <creatorName>Korolija, Ivan</creatorName>
              <givenName>Ivan</givenName>
              <familyName>Korolija</familyName>
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            <creator>
              <creatorName>Rovas, Dimitrios</creatorName>
              <givenName>Dimitrios</givenName>
              <familyName>Rovas</familyName>
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          <titles>
            <title><![CDATA[Building facade images for window states]]></title>
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          <subjects>
            <subject>Building science, technologies and systems</subject>
            <subject>Window states detection</subject>
            <subject>Building facade images</subject>
            <subject>Deep learning</subject>
            <subject>Image augmentation</subject>
            <subject>Building Science and Techniques</subject>
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            <date dateType="Created">2021-08-06</date>
            <date dateType="Updated">2022-03-15</date>
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          <publicationYear>2021</publicationYear>
          <publisher>University College London</publisher>
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            <description descriptionType="Abstract"><![CDATA[The data was used for "Impact of Traditional Augmentation Methods on Window States Detection", which is a conference paper of CLIMA2022. The main purpose of this data is for reproductivity of proposed methods. All images are annotated with XML format using LabelImg. Additionally, this dataset may be used for other object detection and segmentation tasks as a possible application.]]></description>
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