Person re-identification by siamese network

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<title>Person re-identification by siamese network</title>
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<namePart>Newlin Shebiah, R.</namePart>
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<abstract displayLabel="Summary">This paper proposes the use of a Siamese network, which is a neural architecture that takes a pair of images or videos as input and predicts the similarity or dissimilarity of a person across two cameras. The output includes the prediction of similar and dissimilar persons along with their prediction scores. The proposed method was evaluated using iLIDS-VID and PRID 2011 datasets, and achieved recognition accuracy of 79.52% and 85.82%, respectively. These results demonstrate the effectiveness of the Siamese network for person re-identification tasks. Overall, this study contributes to the ongoing research on improving the accuracy of person re-identification across multiple cameras in surveillance videos</abstract>
<note type="statement of responsibility">Newlin Shebiah R...[et al.]</note>
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<title>Revista Iberoamericana de Inteligencia Artificial</title>
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<publisher> : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</publisher>
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<identifier type="issn">1988-3064</identifier>
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<text>13/03/2023 Volumen 26 Número 71 - marzo 2023 , pp. 25-33</text>
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