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Categorical Classification and Deletion of Spam Images on Smartphones Using Image Processing and Machine Learning

机译:使用图像处理和机器学习对智能手机上的垃圾邮件图像进行分类和删除

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摘要

We regularly use communication apps like Facebook and WhatsApp on our smartphones, and the exchange of media, particularly images, has grown at an exponential rate. There are over 3 billion images shared every day on Whatsapp alone. In such a scenario, the management of images on a mobile device has become highly inefficient, and this leads to problems like low storage, manual deletion of images, disorganization etc. In this paper, we present a solution to tackle these issues by automatically classifying every image on a smartphone into a set of predefined categories, thereby segregating spam images from them, allowing the user to delete them seamlessly.
机译:我们经常在智能手机上使用Facebook和WhatsApp等通信应用程序,并且媒体(尤其是图像)的交换呈指数级增长。每天仅在Whatsapp上共享的图像就超过30亿张。在这种情况下,移动设备上的图像管理变得非常低效,这会导致存储量低,图像的手动删除,混乱等问题。在本文中,我们提出了一种通过自动分类来解决这些问题的解决方案智能手机上的每个图像都分为一组预定义的类别,从而将垃圾邮件图像与它们隔离开来,从而允许用户无缝删除它们。

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