面部表情识别方法的实证研究

Marium Malik, Maira Kamran, Syed Muhammad Raza Naqvi
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引用次数: 0

摘要

面部表情识别(FER)在医疗、安全、企业等系统的决策应用中具有重要的影响,是一个备受研究的领域。在本文中,ferf技术的高级概述,数据库和重要研究的分析分四部分进行。首先,讨论了FER在工业应用中的重要性。其次,对最新框架的性能进行了分析。第三,描述了适应性面临的挑战。第四,解决了文献中的空白。该研究表明,FER技术在人工智能应用程序的开发中非常有用,可以通过数据预处理、特征提取、特征选择和表情识别来进行模式分析。所面临的主要挑战与描述级数据有关。本研究为未来希望探索这一领域的研究人员提供了更好的理解和最新的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Empirical Study of Facial Expression Recognition Methods
Facial Expression Recognition (FER) is a field that is being well researched due to its great impact on decision-making application in the domain of medical, security, corporate and other systems. In this paper, a high-level overview of the FER techniques, databases, and analysis of significant research is performed in four-folds. First, the importance of FER applications in the industries is discussed. Second, the performance of the latest frameworks is analyzed. Third, the challenges faced in adaptability are described. Fourth, the gaps in the literature are addressed. The study reveals that FER techniques are useful in the development of AI applications for pattern analysis that work by data pre-processing, feature extraction, feature selection, and expression recognition. The main challenge faced is concerned with description-level data. This study provides a better understanding and updated information for future researchers who wish to explore this domain.
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