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  1. 1

    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.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  2. 2

    Comparison of external and internal training loads in elite junior male tennis players during offensive vs. defensive strategy conditions: a pilot study

    Tóth, P. J., Trzaskoma-Bicsérdy, G., Trzaskoma, L., Négyesi, J., Dobos, K., Havanecz, K., Sáfár, S., Ökrös, C.
    Published in Sports (2025)
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  3. 3

    Using markerless motion analysis to quantify sex and discipline differences in external mechanical work during badminton match play

    Santiano, F., Ison, S., Emmerson, J., Colyer, S.
    Published in Journal of Sports Sciences (2025)
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  4. 4

    Accuracy of an ultra-wideband-based tracking system for time-motion analysis in tennis

    Yang, W., Wang, J., Zhao, Z., Cui, Y.
    Published in Sensors (2025)
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  5. 5

    Characteristics of the match performance of tennis players under 14 years old

    Šanjug, S., Barbaros, P., Bilic, Z.
    Published in 10th International scientific conference on kinesiology. Book of abstracts (2024)
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  6. 6

    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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  7. 7

    Scoring probability model based on service landing location and ranking points in men`s professional tennis matches

    Shimizu, F., Konaka, E.
    Published in International Journal of Sports Science & Coaching (2024)
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  8. 8

    Badminton player`s shot prediction using deep learning

    Ashfaq, F., Jhanjhi, N. Z., Khan, N. A.
    Published in Innovation and Technology in Sports: Proceedings of the International Conference on Innovation and Technology in Sports, (ICITS) 2022, Malaysia (2023)
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  9. 9

    Prediction of shuttle trajectory in badminton using player's position

    Nokihara, Y., Hori, R., Hachiuma, R., Saito, H.
    Published in Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (2023)
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  10. 10

    A query language for exploratory analysis of video-Based tracking data in padel matches

    Javadiha, M., Andujar, C., Lacasa, E. A.
    Published in Sensors (2022)
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  11. 11

    Convolutional neural networks based ball detection in tennis games

    Renò, V., Mosca, N., Marani, R., Nitti, M., D'Orazio, T., Stella, E.
    Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2018)
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  12. 12

    Badminton trajectory accurate tracking and positioning method based on machine vision

    Song, Y., Zeng, Y., Li, P.
    Published in IEEE Xplore (2022)
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  13. 13

    Effective serving strategies in men`s doubles Davis cup matches: an analysis using tracking technology

    Vives, F., Crespo, M., Guzmán, J. F., Martínez-Gallego, R.
    Published in International Journal of Performance Analysis in Sport (2022)
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  14. 14

    Construction of intelligent campus tennis players' body data monitoring and injury warning system based on data fusion

    Li, Y.
    Published in Revista Brasileira de Medicina do Esporte (2021)
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  15. 15

    Automatic badminton action recognition using CNN with adaptive feature extraction on sensor data

    Wang, Y., Fang, W., Ma, J., Li, X., Zhong, A.
    Published in Intelligent computing theories and application (2019)
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  16. 16

    Case study: using video analysis of matches to track player performance and inform training

    Glynn, J.
    Published in Proceedings Book of The 15th ITTF Sports Science Congress Düsseldorf, 27th - 28th May 2017 (2017)
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  17. 17

    Validation of a video-based system for automatic tracking of tennis players

    Petróvna Resende Lara, J., Roveri Vieira, C. L., Shoiti Misuta, M., Arruda Moura, F., Machado Leite de Barros, R.
    Published in International Journal of Performance Analysis in Sport (2018)
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  18. 18

    Validation of ball spin estimates in tennis from multi-camera tracking data

    Cant, O., Kovalchik, S., Cross, R., Reid, M.
    Published in Journal of Sports Sciences (2020)
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  19. 19

    A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis

    Giles, B., Kovalchik, S., Reid, M.
    Published in Journal of Sports Sciences (2020)
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  20. 20

    Ball tracking and trajectory prediction for table-tennis robots

    Lin, H.-I., Yu, Z., Huang, Y.-C.
    Published in Sensors (2020)
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