基于内容的图像检索的当代集成

R. Shaikh, S. Deep, Jian-ping Li, K. Kumar, Asif Khan, I. Memon
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引用次数: 16

摘要

基于内容的图像检索(CBIR)一直是一个具有挑战性的研究领域。人类可以通过记忆判断和响应来获取和定位目标图像,并将其与特定对象联系起来,但对于计算机视觉来说,从复杂的数据库中检索图像是一个具有挑战性的问题,难以用高效的算法来平衡。同时存在的情况和复杂的对象,从图像中检索对象或从数据库中查询图像一直是一个很大的挑战。在本文中,我们提出结合神经网络来感知特定的客观图像,该图像是基于内容的,并且易于从复杂的数据库中检索。
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Contemporary integration of content based image retrieval
Content Based Image Retrieval (CBIR) has been a challenging research area among researchers of both industries and academic institutions. Human can judge and respond by memory to obtain and locate the target image and relate it by specific object, but for computer vision it's a challenging issue to retrieve image from complex database that is difficult to balance with an efficient algorithm. Simultaneous situation and complex object has been always a big challenge to retrieve an object from image or query image from database. In this paper, we propose to combine Neural Network to sense a specific objective image that is content based and easily retrieving from complex database.
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