Pattern Recognition : 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings

Carsten Rother

ISBN 10: 3031546040 / ISBN 13: 9783031546044

Editore: Springer Nature Switzerland, Springer Nature Switzerland, 2024

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Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 45th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2023, which took place in Heidelberg, Germany, during September 19-22, 2023.The 40 full papers included in these proceedings were carefully reviewed and selected from 76 submissions. They were organized in topical sections as follows:Segmentation and action recognition;3D reconstruction and neural rendering;Photogrammetry and remote sensing;Pattern recognition in the life sciences;Interpretable machine learning;Weak supervision and online learning;Robust models.

Codice articolo 9783031546044

Dati bibliografici

• Titolo: Pattern Recognition : 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings
• Editore: Springer Nature Switzerland, Springer Nature Switzerland
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 3031546040
• ISBN 13: 9783031546044
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 36 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 36 millimetri di profondità
• Peso: 984 grammi

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Riassunto

This book constitutes the proceedings of the 45th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2023, which took place in Heidelberg, Germany, during September 19-22, 2023. 

The 40 full papers included in these proceedings were carefully reviewed and selected from 76 submissions. They were organized in topical sections as follows: Segmentation and action recognition; 3D reconstruction and neural rendering; Photogrammetry and remote sensing; Pattern recognition in the life sciences; Interpretable machine learning; Weak supervision and online learning; Robust models.