A Real-Time Recognition System for User Characteristics Based on Deep Learning

Dennis Núñez
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引用次数: 1

Abstract

This paper describes an implementation of a novel real-time recognition system which is capable to identify important information from a single user such as gender, age, emotions and hand gestures. The key of this recognition system is the classification process. This is carried out by using several convolutional neural networks that were designed to achieve a high accuracy rate and acceptable response time making use of low computational resources. As a result, this recognition system could be useful in numerous applications like human-computer interaction, person identification, security control and others.
基于深度学习的用户特征实时识别系统
本文描述了一种新型实时识别系统的实现,该系统能够识别来自单个用户的重要信息,如性别、年龄、情绪和手势。该识别系统的关键是分类过程。这是通过使用几个卷积神经网络来实现的,这些神经网络旨在利用低计算资源实现高准确率和可接受的响应时间。因此,这种识别系统可以在人机交互、人员识别、安全控制等众多应用中发挥作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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