A DIGITAL PRINTING APPLICATION AS AN EXPRESSION IDENTIFICATION SYSTEM

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Arman Arman, Prasetya Prasetya, Feny Nurvita Arifany, Fertilia Budi Pradnyaparamita, Joni Laksito
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引用次数: 0

Abstract

Human Computer Interaction (HCI), a growing research field in science and engineering, aims to provide a natural way for humans to use computers as tools. Humans prefer to interact with each other mainly through speech, but also through facial expressions and gestures, for certain parts of the speech and displays of emotions. The identity, age, gender, and emotional state of a person can be obtained from his face. The impression we receive from the expression reflected on the face affects our interpretation of the spoken word and even our attitude towards the speaker himself. Although emotion recognition is an easy task for humans, it still proves to be a difficult task for computers to recognize user`s emotional state. Advances in this area promise to arm our technological environment by means for more effective interactions with humans, and hopefully the impact of facial expressions on cognition will increase rapidly in the future. Will do. In recent years, the adoption of digital has increased rapidly, and the quality has improved significantly. Digital printing has resulted in fast delivery and needs-based costs. This article describes a sophisticated combination classifier approach, an empirical study of ensembles, stacking, and voting. These three approaches were tested on Nave Bayes (NB), Kernel Naive Bayes (kNB), Neural Network (NN), Auto MultiLayer Perceptron (Auto MLP), and Decision Tree (DT), respectively. The main contribution of this paper is the improvement of the classification accuracy of facial expression recognition tasks. In both persondependent and nonpersondependent experiments we showed that using a combination of these classifier combinations gave significantly better results than using individual classifiers. It has been observed from experiments that the overall voting technique by voting achieves the best classification accuracy.
一种数字印刷作为表情识别系统的应用
人机交互(HCI)是科学和工程领域的一个新兴研究领域,旨在为人类提供一种自然的方式来使用计算机作为工具。人类更喜欢主要通过言语与他人互动,但也会通过面部表情和手势、言语的某些部分和情绪的表达来进行互动。一个人的身份、年龄、性别和情绪状态都可以从他的脸上得到。我们从脸上的表情中得到的印象会影响我们对说话人的理解,甚至影响我们对说话人本身的态度。虽然情绪识别对人类来说是一件容易的事情,但对于计算机来说,识别用户的情绪状态仍然是一项艰巨的任务。这一领域的进步有望通过与人类更有效的互动来武装我们的技术环境,并希望面部表情对认知的影响在未来会迅速增加。会做的事情。近年来,数字化的采用迅速增加,质量也有了显著提高。数字印刷导致了快速交付和基于需求的成本。本文描述了一种复杂的组合分类器方法,对集成、堆叠和投票进行了实证研究。这三种方法分别在自然贝叶斯(NB)、核朴素贝叶斯(kNB)、神经网络(NN)、自动多层感知器(Auto MLP)和决策树(DT)上进行了测试。本文的主要贡献是提高了面部表情识别任务的分类准确率。在个人依赖和非个人依赖的实验中,我们发现使用这些分类器组合的组合比使用单个分类器的结果要好得多。实验表明,通过投票的整体投票技术达到了最好的分类精度。
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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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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