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  1. 1

    Development of a MediaPipe-based framework for biomechanical quantification of table tennis forehand strokes

    Lyu, Y., Duan, X., Yang, C., Ye, Q.
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  2. 2

    TT3D: table tennis 3D reconstruction

    Gossard, T., Ziegler, A., Zell, A.
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  3. 3

    Towards ball spin and trajectory analysis in table tennis broadcast videos via physically grounded synthetic-to-real transfer

    Kienzle, D., Schön, R., Lienhart, R., Satoh, S.
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  4. 4

    Analyse der Olympischen Spiele 2024 im Tischtennis (Analysis of the 2024 Olympic Games in table tennis)

    Nimtz, S., Schwieder, T., Schönburg, S., Prause, R.
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  5. 5

    Muscle synergy analysis during badminton forehand overhead smash: integrating electromyography and musculoskeletal modeling

    Tajik, R., Dhahbi, W., Fadaei, H., Mimar, R.
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  6. 6

    The diversity of movement patterns in the execution of a «Top spin» right-handed stroke in table tennis among elite athletes

    Barchukova, G. V., Vagin, A. Yu., Qian, D.
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  7. 7

    Training mit der Spinsight-App: Ein Mehrwert für das Technik-Training im Verein? (Training with the Spinsight app: Added value for technical training in the club?)

    Geisler, M.
    Published in Trainerbrief (2025)
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  8. 8

    Visualizing victory - Investigating an immersive VR game analysis tool for badminton

    Dänekas, B., Zargham, N., Zhang, S., Vajen, R., Bhattacharjee, S., Khadse, S., Loerakker, M. B., Malaka, R.
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  9. 9

    Video skeletonization and AI: a novel approach for analyzing kinematics in table tennis

    Ferlinghetti, E., Abeni, N., Kumamoto, R., Loh, P. Y., Lancini, M.
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  10. 10

    Enhancing badminton game analysis: an approach to shot refinement via a fusion of shuttlecock tracking and hit detection from monocular camera

    Hsu, Y.-H., Yu, C.-C., Cheng, H.-Y.
    Published in Sensors (2024)
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  11. 11

    Self-controlled video feedback facilitates the learning of tactical skills in tennis

    van der Meer, B. R., van den Hoven, M. A. C., van der Kamp, J., Savelsbergh, G. J. P.
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  12. 12

    Using video analysis and artificial neural network to explore association rules and influence scenarios in elite table tennis matches

    Liu, J. W., Hsu, M. H., Lai, C. L., Wu, S. K.
    Published in The Journal of Supercomputing (2024)
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  13. 13

    Detection of shot information using footwork trajectory and skeletal information of badminton players

    Tanaka, N., Shishido, H., Suita, M., Nishijima, T., Kameda, Y., Kitahara, I.
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  14. 14

    Spin measurement system for table tennis balls based on asynchronous non-high-speed cameras

    Tamaki, S., Yamagata, S., Hashizume, S.
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  15. 15

    Comparative analysis of the techniques and tactics of world excellent badminton men`s and women`s doubles

    Feng, L., Chen, T.
    Published in Advances in Physical Education (2023)
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  16. 16

    Video analysis application to assess the reaction time in an ATP tennis tournament

    Caprioli, L., Campoli, F., Edriss, S., Padua, E., Panichi, E., Romagnoli, C., Annino, G., Bonaiuto, V.
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  17. 17

    Application of video analysis to the measurement of reaction time in high-level tennis competition

    Annino, G., Bonaiuto, V., Campoli, F., Caprioli, L., Edriss, S., Padua, E., Panichi, E., Romagnoli, C.
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  18. 18

    Review of ITF-approved Player Analysis Technology (PAT)

    Vaquer Castillo, A.
    Published in Coaching and Sport Science Review (2023)
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  19. 19

    Die Janova App und der Coach in der Griffschale (The Janova app and the coach in the handle)

    Stützer, S.
    Published in Trainerbrief (2023)
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  20. 20

    Videoanalyse ermöglicht gute Vorbereitung auf die Gegern*innen (Video analysis enables good preparation for the opponents)

    Pauli, C.
    Published in Badminton Sport (2023)
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