Proceedings of the 14th International Symposium on Computer Science in Sport (IACSS 2023) / edited by Hui Zhang, Martin Lames, Arnold Baca, Yingcai Wu

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Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Lecture notes on data engineering and communicationsVerlag: Singapore : Springer Nature Singapore, 2024Verlag: Singapore : Imprint: Springer, 2024Auflage: 1st ed. 2024Beschreibung: 1 Online-Ressource(XXIV, 162 p. 51 illus., 45 illus. in color.)ISBN:

9789819728985

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Andere physische Formen: 9789819728978 | 9789819728992 | 9789819729005 | Erscheint auch als: 9789819728978 Druck-Ausgabe | Erscheint auch als: 9789819728992 Druck-Ausgabe | Erscheint auch als: 9789819729005 Druck-Ausgabe | Erscheint auch als: Proceedings of the 14th International Symposium on Computer Science in Sport (IACSS 2023). Druck-Ausgabe. Heidelberg : Springer Nature, 2024DDC-Klassifikation:

688.7 23

DOI: DOI: 10.1007/978-981-97-2898-5Online-Ressourcen:

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Zusammenfassung: Machine Learning based Automatic Effective Round Segmentation Method for Table Tennis -- Automatic Formation Recognition in Handball Using Template Matching -- A Finite Element Model to Predict Shear Deformation in Running Shoe Midsoles during the Foot Strike.Zusammenfassung: This book is a compilation of selected papers from the 14th International Symposium on Computer Science in Sport (IACSS 2023), held on September 27-30, 2023 in Hangzhou, China. The work focuses on the application of computer science and technology in the field of sports (such as intelligent data collection, data mining, visual analysis of game data, virtual reality, machine learning, computer vision, match prediction models and performance analysis). The contents make valuable contributions to academic researchers, college students, coaches and athletes, and sports management personnel (such as managers of sports associations, training bases, and professional clubs). Additionally, readers will encounter new ideas for realizing a more efficient and convenient training and exercise system.PPN: PPN: 1890095680Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-ENG | ZDB-2-SXE

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