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Virtual Robotic Arm Control with Hand Gesture Recognition and Deep Learning Strategies
Karunya Institute of Technology and Sciences, IND.
Karunya University, IND.
Karunya University, IND.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
2017 (engelsk)Inngår i: Deep Learning for Image Processing Applications, IOS Press BV , 2017, Vol. 31, s. 50-67Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Hand gestures and Deep Learning Strategies can be used to control a virtual robotic arm for real-time applications. A robotic arm which is portable to carry various places and which can be easily programmed to do any work of a hand and is controlled by using deep learning techniques. Deep hand is a combination of both virtual reality and deep learning techniques. It estimated the active spatio-temporal feature and the corresponding pose parameter for various hand movements, to determine the unknown pose parameter of hand gestures by using various deep learning algorithms. A novel framework for hand gestures has been made to estimate by using a deep convolution neural network (CNN) and a deep belief network (DBN). A comparison in terms of accuracy and recognition rate has been drawn. This helps in analyzing the movement of a hand and its fingers which can be made to control a robotic arm with high recognition rate and less error rate. © 2017 The authors and IOS Press. All rights reserved.

sted, utgiver, år, opplag, sider
IOS Press BV , 2017. Vol. 31, s. 50-67
Serie
Advances in parallel Computing, ISSN 0927-5452 ; 31
Emneord [en]
convolution neural network, Deep belief network, Deep learning, hand gesture recognition, kinetic, Restricted Boltzmann Machine, spatio-temporal feature, virtual reality
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-16191DOI: 10.3233/978-1-61499-822-8-50Scopus ID: 2-s2.0-85046353694ISBN: 9781614998211 (tryckt)OAI: oai:DiVA.org:bth-16191DiVA, id: diva2:1206996
Tilgjengelig fra: 2018-05-18 Laget: 2018-05-18 Sist oppdatert: 2018-08-21bibliografisk kontrollert

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