Gesture Identification Based on Neural Network
Tamilarasu Viswanathan1, M. Mathankumar2, R. Ramya3
1Tamilarasu Viswanathan, Assistant Professor, 3Kumaraguru College of Technology Coimbatore (Tamil Nadu), India.
2M.Mathankumar, Assistant Professor, Kumaraguru College of Technology Coimbatore (Tamil Nadu), India.
3R.Ramya, PG Scholar, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology Coimbatore (Tamil Nadu), India.
Manuscript received on 13 December 2018 | Revised Manuscript received on 22 December 2018 | Manuscript Published on 30 December 2018 | PP: 418-420 | Volume-8 Issue-2S, December 2018 | Retrieval Number: 100.1/ijeat.B10871282S18/18©BEIESP
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Abstract: This paper presented a Gesture based interaction has a wide run of applications in a computing environment, which is a normal way of human machine interaction. It gives an productive human-machine interaction for intuitively and shrewdly computing. The accelerometer sensor is utilized for information securing. The motion acknowledgement basically comprises of two stages: Training and Testing stage. The training stage is performed offline and it comprises of collection of speeding up signals from the accelerometer sensor and the highlight extraction of the speeding up signals. The testing organize is done online. In this venture, two signals are utilized with two highlights. All the two signals are prepared utilizing a single arrange. The strategy utilized to prepare the signals is Extraordinary Learning Machines (ELM) which is a sort of neural organize. The calculation is recreated in overshadow and actualized in arduino for genuine time. The exactness watched for all the three signals is more than 90%.
Keywords: Gesture, Gesture Recognition, Arduino, Neural Network, Machine Learning.
Scope of the Article: Network Protocols & Wireless Networks