摘要
一位新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-在一份新的报告中讨论了人工智能的研究结果。根据NewsRx记者从伊拉克巴格达发回的新闻报道，研究表明：“面部表情识别(FER)系统通过提取面部特征来准确识别面部表情。”我们的新闻记者引用了Al-Iraqia Universit Y的一篇研究文章:“在这个过程中,鲁棒性人脸特征的提取是在自动人脸检测之后完成的。在FAR2013数据集上,我们开发了一个五步系统来评估机器学习算法的性能。该系统包括预处理、特征提取、模型训练和测试、分类和识别。”本研究使用了三种机器学习算法:逻辑回归(LR)、随机森林(RF)和AdaBoost(ADA)。RF算法精度最高,成功率为61%。本研究的目的是评价机器学习算法在FAR2013数据集上的性能。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Research findings on artificial intelligence are discussed in a new report. According to news reporting originating from Baghdad, Iraq, by NewsRx correspondents, research stated, "Facial expression recognition (FER) systems accurately identify facial expressions by extracting facial featu res." Our news journalists obtained a quote from the research from Al-Iraqia Universit y: "The extraction of robust facial features comes after automatic face detectio n in this procedure. On the FAR2013 dataset, a five-step system developed to ass ess the performance of machine learning algorithms. Components of the system inc lude preprocessing, feature extraction, model training and testing, classificati on, and evaluation. Three machine-learning algorithms utilized in this study: lo gistic regression (LR), random forest (RF), and AdaBoost (ADA). The RF algorithm achieved the highest degree of precision with a 61% success rate. The purpose of the study was to evaluate the performance of machine learning al gorithms on the FAR2013 dataset."
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