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Person re-identification by siamese network

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001  MAP20230009932
003  MAP
005  20231214131729.0
008  230519e2023 esp|||p |0|||b|eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
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24500‎$a‎Person re-identification by siamese network ‎$c‎Newlin Shebiah R...[et al.]
520  ‎$a‎This 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
650 4‎$0‎MAPA20080611200‎$a‎Inteligencia artificial
650 4‎$0‎MAPA20080563790‎$a‎Predicciones
650 4‎$0‎MAPA20080586331‎$a‎Métodos analíticos
650 4‎$0‎MAPA20080608712‎$a‎Sistemas de Vigilancia
7001 ‎$0‎MAPA20230004043‎$a‎Newlin Shebiah, R.
7730 ‎$w‎MAP20200034445‎$g‎13/03/2023 Volumen 26 Número 71 - marzo 2023 , pp. 25-33‎$x‎1988-3064‎$t‎Revista Iberoamericana de Inteligencia Artificial‎$d‎ : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-
85600‎$y‎MÁS INFORMACIÓN‎$u‎ mailto:centrodocumentacion@fundacionmapfre.org?subject=Consulta%20de%20una%20publicaci%C3%B3n%20&body=Necesito%20m%C3%A1s%20informaci%C3%B3n%20sobre%20este%20documento%3A%20%0A%0A%5Banote%20aqu%C3%AD%20el%20titulo%20completo%20del%20documento%20del%20que%20desea%20informaci%C3%B3n%20y%20nos%20pondremos%20en%20contacto%20con%20usted%5D%20%0A%0AGracias%20%0A