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A study of factors that influence the accuracy of content-based geospatial ranking systems

机译:影响基于内容的地理空间排名系统准确性的因素的研究

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摘要

Visual patterns found in geospatial images are complex, dynamic and difficult to be articulated by human analysts; let alone building a computational model to understand the intertwining semantics in the images. Advancements in image collection and pre-processing have led to a need for identifying the factors that affect content-based geospatial retrieval systems. In this article, we study the factors that influence the semantic assignment precision when varying semantic space complexity and training set size. We test their influence using different data mining algorithms. Our findings provide some new insights for future research in training image retrieval systems under various conditions related to semantic mixture, feature space overlapping and size of training data set.
机译:在地理空间图像中发现的视觉模式是复杂的,动态的,并且人类分析人员难以表达。更不用说构建计算模型来理解图像中相互交织的语义了。图像收集和预处理的进步导致需要确定影响基于内容的地理空间检索系统的因素。在本文中,我们研究了在改变语义空间复杂度和训练集大小时影响语义分配精度的因素。我们使用不同的数据挖掘算法测试它们的影响。我们的发现为将来在与语义混合,特征空间重叠和训练数据集大小有关的各种条件下的训练图像检索系统中的研究提供了新的见识。

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