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AN APPROACH FOR CBIR SYSTEM THROUGH ADAPTIVE RESONANCE THEORY (ART1)

机译:自适应共振理论的CBIR系统方法(ART1)

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In these days an image retrieval system has become a challenging task. Many systems based on the text based retrieval but the need of image based retrieval system that takes an image as the input query and retrieves images based on image content is more complicated task. Content Based Image Retrieval is an approach for retrieving semantically-relevant images from an image database based on automatically-derived image features. The aim and Objective of the Paper is classifying the soils using Adaptive resonance theory, a Neural Network concepts for more efficient and effective results. Forthcoming problems or disasters are easily studied and predicted with help of ART .So that priory we can rescue the human kind and mother earth.
机译:如今,图像检索系统已成为一项具有挑战性的任务。许多基于基于文本的检索的系统,但是需要基于图像的检索系统(将图像作为输入查询并基于图像内容检索图像)是更加复杂的任务。基于内容的图像检索是一种基于自动派生的图像特征从图像数据库中检索与语义相关的图像的方法。本文的目的是使用自适应共振理论对土壤进行分类,自适应共振理论是一种神经网络概念,可以实现更有效的结果。借助ART,可以轻松地研究和预测即将到来的问题或灾难。因此,我们可以优先保护人类和大地。

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