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김건우(K.-W. Kim),장규삼(G.-S. Jang),임세민(S.-M. Lim),안인경(I.-K. Ahn),박주영(J. Park),오형철(H.-C. Oh) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.8
This paper proposes a system that recognizes a person’s activity from the data, collected during a initial short interval of time, for the motion which he/she takes. Eight designs of RNNs (recurrent neural networks) are considered to identify which skills (stroke, drive, short, etc) that a table-tennis player takes. We show that the designs based on GRU (Gated Recurrent Units) require significantly less parameters but perform better than other designs.