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Image classification using neural networks and ontologies

机译:使用神经网络和本体进行图像分类

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The advent of extremely powerful home PC and the growth of the Internet have made the appearance of multimedia documents a common sight in the computer world. In the world of unstructured data composed of images and other media types, classification often comes at the price of countless hours of manual labor. This research aims to present a scalable system capable of examining images and accurately classifying the image based on its visual content. When retrieving images based on a user's query, the system yields a minimal amount of irrelevant information (high precision) and ensures a maximum amount of relevant information (high recall).
机译:功能强大的家用PC的出现和Internet的发展,使多媒体文档的出现在计算机世界中屡见不鲜。在由图像和其他媒体类型组成的非结构化数据世界中,分类通常是以无数小时的体力劳动为代价的。这项研究旨在提供一种可扩展的系统,该系统能够检查图像并根据其视觉内容对图像进行准确分类。当基于用户的查询检索图像时,系统产生最少数量的不相关信息(高精度),并确保最大数量的相关信息(高度召回)。

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