基于人脸图像的实时性别识别,你只看一眼(yolo)

V. K, C. Ramachandran
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引用次数: 8

摘要

性别认同是目前研究的一个重要领域。有许多使用不同架构的性别预测系统。本文提出了一种基于人脸图像的实时性别预测系统。使用的技术是You Only Look Once (YOLO) v3目标检测算法。暗网是用来训练的。Keras和OpenCV用于测试。使用的数据集是IMDb,谷歌印度图像和一些使用移动相机拍摄的印度自定义图像的组合。测试图像的准确率为84.69%。labeliming是用于标记人脸图像的软件。建议的工作目的是在监测、安全等方面使用该系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time Gender Identification from Face Images using you only look once (yolo)
Gender identification is an important area under which the researches are still going on. There are many gender prediction systems made using different architectures. This paper presents a real-time system which can be used for gender prediction from face images. The technique used is You Only Look Once (YOLO) v3 object detection algorithm. Darknet is used for training. Keras and OpenCV are used for testing. The dataset used is a combination of IMDb, Google Indian images and some Indian custom images taken using mobile camera. The test image accuracy was found to be 84.69%. Labelimg is the software used for labeling the face images. The aim of the proposed work is to use the system in case of monitoring, security concerned areas etc.
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