设计一种智能手机恶意图像检测认知工具

Hiroyuki Nishiyama, F. Mizoguchi
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引用次数: 1

摘要

在这项研究中,我们设计了一个认知工具来检测智能手机上的恶意图像。该工具可以学习智能手机相机拍摄的图像,并自动将新图像分类为智能手机中的恶意图像。为了开发学习分类器工具,我们使用支持向量机(SVM)在智能手机上实现了图像分析功能和学习分类器功能。通过该工具,用户可以使用智能手机的摄像头采集图像数据,创建学习数据,并根据智能手机中的学习数据对新的图像数据进行分类。在本研究中,我们将该工具应用于化妆品推荐服务系统的用户界面,并通过减少该服务中诊断服务器的负载和改善用户服务来证明其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a cognitive tool to detect malicious images using the smart phone
In this study, we design a cognitive tool to detect malicious images using a smart phone. This tool can learn shot images taken with the camera of a smart phone and automatically classify the new image as an malicious image in the smart phone. To develop the learning and classifier tool, we implement an image analysis function and a learning and classifier function using a support vector machine (SVM) with the smart phone. With this tool, the user can collect image data with the camera of a smart phone, create learning data, and classify the new image data according to the learning data in the smart phone. In this study, we apply this tool to a user interface of a cosmetics recommendation service system and demonstrate its effectiveness by in reducing the load of the diagnosis server in this service and improving the user service.
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