Human‐like sign‐language learning method using deep learning

Autor:	Yangho Ji, Sunmok Kim, Young‐Joo Kim, Ki‐Baek Lee
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	CNN deep learning sign language Telecommunication TK5101-6720 Electronics TK7800-8360
Zdroj:	ETRI Journal, Vol 40, Iss 4, Pp 435-445 (2018)
Druh dokumentu:	article
ISSN:	1225-6463 2233-7326
DOI:	10.4218/etrij.2018-0066
Popis:	This paper proposes a human‐like sign‐language learning method that uses a deep‐learning technique. Inspired by the fact that humans can learn sign language from just a set of pictures in a book, in the proposed method, the input data are pre‐processed into an image. In addition, the network is partially pre‐trained to imitate the preliminarily obtained knowledge of humans. The learning process is implemented with a well‐known network, that is, a convolutional neural network. Twelve sign actions are learned in 10 situations, and can be recognized with an accuracy of 99% in scenarios with low‐cost equipment and limited data. The results show that the system is highly practical, as well as accurate and robust.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/e768e0b1e371485793d2ebb56d64348d Zobrazit plný text záznamu Plný text View record in DOAJ