Intelligent Systems and Pattern Recognition [electronic resource] : Third International Conference, ISPR 2023, Hammamet, Tunisia, May 11-13, 2023, Revised Selected Papers, Part I / edited by Akram Bennour, Ahmed Bouridane, Lotfi Chaari.

Colaborador(es): Bennour, Akram [editor.] | Bouridane, Ahmed [editor.] | Chaari, Lotfi [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Communications in Computer and Information Science ; 1940Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XXI, 286 p. 200 illus., 118 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031463358Tema(s): Artificial intelligence | Machine learning | Application software | Image processing -- Digital techniques | Computer vision | Artificial Intelligence | Machine Learning | Computer and Information Systems Applications | Computer Imaging, Vision, Pattern Recognition and GraphicsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342TA347.A78Recursos en línea: Libro electrónicoTexto En: Springer Nature eBookResumen: This volume constitutes selected papers presented during the Third International Conference on Intelligent Systems and Pattern Recognition, ISPR 2023, held in Hammamet, Tunisia, in May 2023. The 44 full papers presented were thoroughly reviewed and selected from the 129 submissions. The papers are organized in the following topical sections: computer vision; data mining; pattern recognition; machine and deep learning.
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This volume constitutes selected papers presented during the Third International Conference on Intelligent Systems and Pattern Recognition, ISPR 2023, held in Hammamet, Tunisia, in May 2023. The 44 full papers presented were thoroughly reviewed and selected from the 129 submissions. The papers are organized in the following topical sections: computer vision; data mining; pattern recognition; machine and deep learning.

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