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Journal of ShangHai University of Electric Power :2016,32(3):277-282
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人体学输入设备轨迹识别与功能增强
(上海电力学院 计算机科学与技术学院)
Enhancing Human Input Device Features Based on Orbit Recognition
(School of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China)
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Received:May 16, 2015    
中文摘要: 随着机器学习技术在轨迹识别中的广泛应用,提出了一种基于人工神经网络的浏览器鼠标手势扩展算法.该算法通过对轨迹进行分类并与动作建立映射来实现鼠标手势功能,可有效地识别各种复杂的轨迹并准确执行相应的动作.实验结果表明,该方法明显提高了用户的操作体验.
Abstract:With machine learning technology widely used in the orbit recognition,a browser mouse gestures extension based on an artificial neural network is presented.The extension implements mouse gestures function by classifying and mapping orbits.Experimental results show that the extension can effectively identify a variety of complex orbits and execute the appropriate instructions,and can significantly improve the user experience.
文章编号:20160315     中图分类号:    文献标志码:
基金项目:上海市自然科学基金(11ZR1414300);上海市教育委员会科研创新项目(11YZ194).
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