Název: | AICO, Artificial Intelligent COach |
Autoři: | Marco, Vicent Sanz Ukita, Norimichi Kobayashi, Natsuko Matsuoka, Morito |
Citace zdrojového dokumentu: | Journal of WSCG. 2020, vol. 28, no. 1-2, p. 27-36. |
Datum vydání: | 2020 |
Nakladatel: | Václav Skala - UNION Agency |
Typ dokumentu: | článek article |
URI: | http://wscg.zcu.cz/WSCG2020/2020-J_WSCG-1-2.pdf http://hdl.handle.net/11025/38422 |
ISSN: | 1213-6972 (print) 1213-6980 (CD-ROM) 1213-6964 (on-line) |
Klíčová slova: | počítačové vidění;zpracování obrazu a videa;rozpoznávání vzorů;sport;UI;Umělá inteligence |
Klíčová slova v dalším jazyce: | computer vision;image and Video Processing;pattern recognition;sport;AI;Artificial Intelligence |
Abstrakt v dalším jazyce: | Choosing effective strategies before playing against an opponent team is a laborious task and one of the main challenges that American football coaches have to cope with. For this reason, we have developed an artificial intelligent American football coach (AICO), a novel system which helps coaches to decide the best defensive strategies to be used against an opponent. Similar to coaches who prepare a winning game plan based on their vast experience and previously obtained opponents’ statistics, AICO uses power of machine learning and video analysis. Tracking every player of the last recorded matches of the opponent team, AICO learns the strategies used by them and then calculates how successfully their own defensive strategies will perform against them. We have used 7350 videos in our experiments obtaining that AICO can recognize the opponent’s strategies with about 93% accuracy and provides the successful rate of each strategy to be used against them with 94% accuracy. |
Práva: | © Václav Skala - UNION Agency |
Vyskytuje se v kolekcích: | Volume 28, Number 1-2 (2020) |
Soubory připojené k záznamu:
Soubor | Popis | Velikost | Formát | |
---|---|---|---|---|
Marco.pdf | Plný text | 9,4 MB | Adobe PDF | Zobrazit/otevřít |
Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam:
http://hdl.handle.net/11025/38422
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