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  1. 1

    The classification of technical devices in the training process of athletes playing games

    Guba V. P., Rodin A. V., Skripko A. D., Pleshakov A. A.
    Published in Theory and Practice of Physical Culture (2025)
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  2. 2

    Assessment of 16-year-old female basketball players with chronojump system

    Borukova, M., Kalinov, I.
    Published in Journal of Applied Sports Sciences (2024)
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  3. 3

    A systematic review of sport-related packages within the R CRAN repository

    Casals, M., Fernández, J., Martínez, V., Lopez, M., Langohr, K., Cortés, J.
    Published in International Journal of Sports Science & Coaching (2023)
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  4. 4

    Spielanalyse im Basketball (Basketball game analysis)

    König, S., Heckel, J.
    Published in Spielanalyse im Sportspiel (2022)
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  5. 5

    Application of deep learning methods for detection and tracking of players

    Ivasic-Kos, M., Host, K., Pobar, M.
    Published 2022
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  6. 6

    Machine learning and the NBA Game

    Georgievski, B., Vrtagic, S.
    Published in Journal of Physical Education and Sport (2021)
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  7. 7

    Neuer Service der RTK: DHB-TrainercenterTV - Das digitale Handwerkszeug für alle Trainer (New service of the RTK: DHB-TrainercenterTV - The digital tool for all trainers )

    Beppler, J.
    Published in Handballtraining (2021)
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  8. 8

    As seen on TV: Automatic basketball video production using Gaussian-based actionness and game states recognition

    Quiroga, J., Carrillo, H., Maldonado, E., Ruiz, J., Zapata, L. M.
    Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2020)
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  9. 9

    Quantifying throwing load in handball: a method for measuring the number of throws

    Skejø, S. D., Liaghat, B., Jakobsen, C. C., Møller, M., Bencke, J., Papi, G., Kunwald, N. P., Sorensen, H.
    Published in Sports Biomechanics (2021)
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  10. 10

    Descriptive and kinetic analysis of two different vertical jump tests among youth and adolescent male basketball athletes using a supervised machine learning approach

    Gillett, J., De Witt, J., Stahl, C. A., Martinez, D., Dawes, J. J.
    Published in The Journal of Strength and Conditioning Research (2021)
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  11. 11

    Innovacionnaja tehnologija komp'juternogo testirovanija psihomotoriki v sportivnyh igrah (Innovative technology in computer testing of psycho-motor in team sports)

    Lisenchuk, G., Tyshchenko, V.
    Published in Science in Olympic Sport (2019)
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  12. 12

    Wer nicht fragt, der nicht gewinnt. Vereins- und mannschaftsinterne Anpassungen auf der Basis einer Saisonauswertung per individuellem Online-Fragebogen (If you don't ask, you don't win. Club- and team-internal adjustments on the basis of a season evaluation with individual online questionnaire)

    Grgic, M.
    Published in Handballtraining (2021)
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  13. 13

    Accuracy and reliability of Sage Analytics tracking system based on UWB technology for indoor team sports

    Hulka, K., Strniste, M., Prycl, D.
    Published in International Journal of Performance Analysis in Sport (2020)
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  14. 14

    Performance prediction and evaluation in female handball players using machine learning models

    Oytun, M., Tinazci, C., Sekeroglu, B., Acikada, C., Yavuz, H. U.
    Published in IEEE Access (2020)
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  15. 15

    A graded concept of an information model for evaluating performance in team handball

    Schwenkreis, F.
    Published in Proceedings of the 8th International Conference on Data Science, Technology and Applications (2019)
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  16. 16

    Active player detection in handball videos using optical flow and STIPs based measures

    Ivasic-Kos, M., Pobar, M., Gonzàlez, J.
    Published in 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS) (2019)
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  17. 17

    Mask R-CNN and optical flow based method for detection and marking of handball actions

    Pobar, M., Ivasic-Kos, M.
    Published in 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) (2018)
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  18. 18

    Building a labeled dataset for recognition of handball actions using mask R-CNN and STIPS

    Ivasic-Kos, M., Pobar, M.
    Published in 2018 7th European Workshop on Visual Information Processing (EUVIP) (2018)
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  19. 19

    Detection of the leading player in handball scenes using Mask R-CNN and STIPS

    Pobar, M., Ivasic-Kos, M.
    Published in Eleventh International Conference on Machine Vision (2019)
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  20. 20

    Model-based behavioral causality analysis of handball with delayed transfer entropy

    Itoda, K., Watanabe, N., Takefuji, Y.
    Published in Procedia - Computer Science (2015)
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