Hand gesture is one of the most important means of touchless communicationbetween human and machines. There is a great interest for commanding electronicequipment in surgery rooms by hand gesture for reducing the time of surgery andthe potential for infection. There are challenges in implementation of a handgesture recognition system. It has to fulfill requirements such as highaccuracy and fast response. In this paper we introduce a system of hand gesturerecognition based on a deep learning approach. Deep learning is known as anaccurate detection model, but its high complexity prevents it from beingfabricated as an embedded system. To cope with this problem, we applied somechanges in the structure of our work to achieve low complexity. As a result,the proposed method could be implemented on a naive embedded system. Ourexperiments show that the proposed system results in higher accuracy whilehaving less complexity in comparison with the existing comparable methods.
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