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Pattern Recognition 46th DAGM German Conference, DAGM GCPR 2024, Munich, Germany, September 10–13, 2024, Proceedings, Part II /

This 2-volume set LNCS 15297-15298 constitutes the refereed proceedings of the 46th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2024, held in Munich, Germany, during September 10-13, 2024. The 44 full papers included in these proceedings were carefully reviewed and...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Cremers, Daniel (Editor), Lähner, Zorah (Editor), Moeller, Michael (Editor), Nießner, Matthias (Editor), Ommer, Björn (Editor), Triebel, Rudolph (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edition:1st ed. 2025.
Series:Lecture Notes in Computer Science, 15298
Subjects:
Image processing > Digital techniques.
Computer vision.
Artificial intelligence.
Computer systems.
Education > Data processing.
Application software.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Artificial Intelligence.
Computer System Implementation.
Computers and Education.
Computer and Information Systems Applications.
Online Access:https://doi.org/10.1007/978-3-031-85187-2
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Summary:This 2-volume set LNCS 15297-15298 constitutes the refereed proceedings of the 46th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2024, held in Munich, Germany, during September 10-13, 2024. The 44 full papers included in these proceedings were carefully reviewed and selected from 81 submissions. They are organized in these topical sections: Part I: Clustering and Segmentation; Learning Techniques; Medical and Biological Applications; Uncertainty and Explainability. Part II: Modelling of Faces and Shapes; Image Generation and Reconstruction; 3D Analysis and Sythesis; Video Analysis; Photogrammetry and Remote Sensing.
Physical Description:1 online resource (XVII, 367 p. 157 illus.). 121 illus. in color.
ISBN:9783031851872
ISSN:1611-3349 ;
DOI:10.1007/978-3-031-85187-2

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