Pattern Recognition : 44th DAGM German Conference, DAGM GCPR 2022, Konstanz, Germany, September 27–30, 2022, Proceedings / / edited by Björn Andres, Florian Bernard, Daniel Cremers, Simone Frintrop, Bastian Goldlücke, Ivo Ihrke

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (607 pages)
• Disciplina: 152.1423; 006.42
• Soggetto topico: Image processing - Digital techniques; Computer vision; Artificial intelligence; Computer engineering; Computer networks; Computer systems; Education - Data processing; Computer Imaging, Vision, Pattern Recognition and Graphics; Artificial Intelligence; Computer Engineering and Networks; Computer System Implementation; Computers and Education
• Persona (resp. second.): AndresBjö
• Nota di contenuto: Machine Learning Methods -- Unsupervised, Semi-supervised and Transfer Learning -- Interpretable Machine Learning -- Low-level Vision and Computational Photography -- Motion, Pose Estimation and Tracking -- 3D Vision and Stereo -- Detection and Recognition -- Language and Vision -- Scene Understanding -- Photogrammetry and Remote Sensing -- Pattern Recognition in the Life and Natural Sciences -- Systems and Applications.
• Sommario/riassunto: This book constitutes the refereed proceedings of the 44th DAGM German Conference on Pattern Recognition, DAGM GCPR 2022, which was held during September 27 – 30, 2022. The 37 papers presented in this volume were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: machine learning methods; unsupervised, semi-supervised and transfer learning; interpretable machine learning; low-level vision and computational photography; motion, pose estimation and tracking; 3D vision and stereo; detection and recognition; language and vision; scene understanding; photogrammetry and remote sensing; pattern recognition in the life and natural sciences; systems and applications.
• Titolo autorizzato: Pattern Recognition
• ISBN: 9783031167881; 3031167880
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910595040203321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 13485