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            <name>Title</name>
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                <text>Articles</text>
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    <name>Article</name>
    <description>Faculty Publications -Articles</description>
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        <element elementId="50">
          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>Ear Recognition Using Rank Level Fusion of Classifiers Outputs</text>
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        <element elementId="49">
          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>BSIF; decision level fusion; ear biometrics; GLBP; HOG; rank level fusion</text>
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              <text>An individuals authentication plays a vital role in our daily life. In the last decade, biometric-based authentication has become more prevalent than traditional approaches like passwords and pins. Ear recognition has gained attention in the biometric community in recent years. Researchers defined several features for the identification of a person from ear image. The features play a vital role in the success of classification models. This paper considers an ensemble of features for designing a new classification model. The features are assessed in isolation as well as through feature-level fusion. Subsequently, a rank-level fusion for classification is introduced. The experiments are conducted on both constrained and unconstrained ear datasets. The results are promising and open up new possibilities in machine learning-based ear recognition  2023, International journal of online and biomedical engineering.All Rights Reserved.</text>
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          <name>Creator</name>
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              <text>Resmi K.R.; Joseph S.M.; Raju G.; Swain D.; Das O.P.; Acharya B.</text>
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              <text>International journal of online and biomedical engineering, Vol-19, No. 3, pp. 127-143.</text>
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          <name>Publisher</name>
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              <text>International Association of Online Engineering</text>
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          <name>Date</name>
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              <text>2023-01-01</text>
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          <name>Identifier</name>
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              <text>&lt;a href="https://doi.org/10.3991/ijoe.v19i03.36831" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.3991/ijoe.v19i03.36831&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151998115&amp;amp;doi=10.3991%2Fijoe.v19i03.36831&amp;amp;partnerID=40&amp;amp;md5=f28e77700baad2a2a883f2ce98eee471" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151998115&amp;amp;doi=10.3991%2fijoe.v19i03.36831&amp;amp;partnerID=40&amp;amp;md5=f28e77700baad2a2a883f2ce98eee471&lt;/a&gt;</text>
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          <name>Rights</name>
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              <text>All Open Access; Gold Open Access</text>
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          <name>Relation</name>
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              <text>ISSN: 26268493</text>
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              <text>Online</text>
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          <name>Language</name>
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              <text>English</text>
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          <name>Type</name>
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              <text>Resmi K.R., CHRIST University, Bengaluru, India; Joseph S.M., Mahatma Gandhi College, Iritty, India; Raju G., CHRIST University, Bengaluru, India; Swain D., Department of Computer Science and Engineering, Pandit Deendayal Energy University, Gandhinagar, India; Das O.P., GSK India Global Services Private Limited, Bangalore, India; Acharya B., Department of Computer Engineering-AI, Marwadi University, Rajkot, India</text>
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