A Noble Gestures Control System Using Machine Learning

CHOONSUNG, NAM and DONG RYEOL, SHIN and EARL, KIM and JANG YEOL, LEE and JUN HEON, KIM (2017) A Noble Gestures Control System Using Machine Learning. In: Sixth International Conference on Advances in Computing, Control and Networking - ACCN 2017, 25-26 February 2017, Bangkok, Thailand.

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Abstract

In this paper, we propose a method to improve the recognition rate of gestures motion and scalability problem which can occur in gestures when operate drone using machine learning. For these purposes, the gestures data transmitted from the drone controller are used for machine learning on real time, and a new learning model is periodically created using the gestures data stored in the HDFS(Hadoop Distributed File System). The goal of our proposed system is to increase the recognition rate of the gestures motion when new learning model is created. In addition, it is possible to expect enhanced scalability through recognition of gestures motion, and that drone is able to recognize a new gestures motion which is not defined in the server.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Big Data, Apache Flume, HDFS, Apache Spark
Depositing User: Mr. John Steve
Date Deposited: 18 Mar 2019 05:31
Last Modified: 18 Mar 2019 05:31
URI: http://publications.theired.org/id/eprint/568

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