S. Shanmugam, Lakshmanan S A, P. Dhanasekaran, P. Mahalakshmi, A. Sharmila
{"title":"Hand Gesture Recognition using Convolutional Neural Network","authors":"S. Shanmugam, Lakshmanan S A, P. Dhanasekaran, P. Mahalakshmi, A. Sharmila","doi":"10.1109/i-PACT52855.2021.9696463","DOIUrl":null,"url":null,"abstract":"The implicit message is usually brought to the spectators through activities involving various body parts like hands, face and arms. This is prominently known as Gesture and many such gestures are generally performed through hands in an involuntary manner. Smartness is to keep tabs on these hand gestures and derive purposeful details out of it. Convolutional neural networks (CNN) track these complex movements and help in extracting prime features. In this paper, training and testing were done consecutively with the aid of images to check the effectiveness of CNN and results are presented.","PeriodicalId":335956,"journal":{"name":"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i-PACT52855.2021.9696463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The implicit message is usually brought to the spectators through activities involving various body parts like hands, face and arms. This is prominently known as Gesture and many such gestures are generally performed through hands in an involuntary manner. Smartness is to keep tabs on these hand gestures and derive purposeful details out of it. Convolutional neural networks (CNN) track these complex movements and help in extracting prime features. In this paper, training and testing were done consecutively with the aid of images to check the effectiveness of CNN and results are presented.