@techreport{oai:ipsj.ixsq.nii.ac.jp:00222385,
 author = {藤原, 円央 and 宍戸, 英彦 and 亀田, 能成 and 北原, 格 and Mao, Fujiwara and Hidehiko, Shishido and Yoshinari, Kameda and Itaru, Kitahara},
 issue = {12},
 month = {Nov},
 note = {近年，日本の卓球競技ではデータ分析が活発に行われており，オリンピックではナショナルチームが映像分析によって得られたラリーに関する情報を選手や監督に提供し，それらの情報が戦術立案に活用された．ラリーに関する情報とは，サービス，レシーブと得失点の傾向，得点の推移，各打球のコース，打法などのことである．打法は種類が多く，似通った打法があるため上級者でも 1 度動画を見ただけで完全に見分けることは困難である．そこで本研究では，戦術分析に適したクラス分けによる打法認識手法の実現を目標とする．ニューラルネットワークを用いた打法認識手法を提案し，その有効性を検証した．, In recent years, data analysis has been actively conducted in Japanese table tennis competitions. At the Olympic Games, the national team provided players and coaches with information on rallies obtained through video analysis, and this information was used for tactical planning. The information on rallies includes Trends in Service, Receiving and Gains and Losses, changes in points, the course of each hit, and strokes. There are many different types of strokes, and they are so similar that it has become difficult for even advanced players to completely distinguish them from each other just by watching a video once. Therefore, the goal of this research is to realize a stroke recognition method based on classifications suitable for tactical analysis. We proposed a stroke recognition method using a neural network and verified its effectiveness.},
 title = {卓球競技映像における深層学習を用いた打法認識手法},
 year = {2022}
}