PEMBUATAN PERANGKAT LUNAK UNTUK KLASIFIKASI JENIS KELAMIN BERDASARKAN CITRA WAJAH

Haris Anggriawan, Nor Hikmah
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引用次数: 1

Abstract

In this study, the 2DPCA feature extraction method and SOM classification were used to classify human sex based on facial images. The trial was conducted on 100 facial images consisting of 50 male facial images and 50 female facial images. The 100 facial image data used were divided into 70 training data and 30 test data. Based on the test results, the best accuracy obtained is 86.67% using a start learning rate of 0.6 and a maximum iteration of 10000. level of accuracy, where a larger maximum iteration value results in a higher level of accuracy.  
基于面部图像的性别分类软件创建
本研究采用2DPCA特征提取方法和SOM分类方法对人脸图像进行性别分类。实验对100张面部图像进行了分析,其中包括50张男性面部图像和50张女性面部图像。使用的100张人脸图像数据分为70张训练数据和30张测试数据。根据测试结果,在起始学习率为0.6,最大迭代次数为10000次的情况下,获得的最佳准确率为86.67%。精度级别,其中最大迭代值越大,精度级别越高。
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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