基于卷积神经网络的物体检测和人脸识别的社交辅助机器人交互

Dendi Hazik Fuadi, D. Novita, Mohammad Taufik
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引用次数: 2

摘要

机器人技术已经发展到在许多方面帮助人类。它不仅限于协助,而且还与人类进行社交互动。机器人可以利用基于机器学习的人工智能概念与人类进行社交互动。在本文中,社交辅助机器人(SAR)的原型通过使用基于卷积神经网络的物体检测和人脸识别以及向Telegram Apps的通信报告来实现人工智能。要进行口头互动,就需要谷歌助手。该原型成功创建,社交互动机器人的平均人脸识别准确率为85.41%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Socially Assistive Robot Interaction by Objects Detection and Face Recognition on Convolutional Neural Network for Parental Monitoring
The technology of robots has developed to help humans in many ways. It is not only limited to assist but also to interact socially with humans. Robots can interact socially with humans by utilizing the concept of artificial intelligence based on machine learning. In this paper, the prototype of Socially Assistive Robot (SAR) implemented artificial intelligence by using object detection and face recognition based on convolutional neural network and communication reports to Telegram Apps. To interact verbally, Google Assistant was required. The prototype was a successfully created and social interaction robot with an average face recognition accuracy is 85.41%.
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