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An Approach to Estimation of Residential Housing Type Based on the Analysis of Parked Cars

机译:基于停放汽车分析的住宅类型估算方法

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A method for prediction of residential housing types based on an analysis of the number of cars parked near buildings in consideration is proposed in the paper. The source of data constitute satellite or aerial images of a given residential area where cars and building can be identified. The machine learning models are build based on the distribution of car parked in the area. The resulting classification models allow for distinguishing between low-rise, mid-rise and high-rise housing. The effectiveness of the method was proved using aerial images of three residential districts of a big city in Poland and the WEKA data mining system.
机译:本文提出了一种基于对考虑在建筑物附近停放的汽车数量进行分析的住宅类型预测方法。数据源构成可以识别汽车和建筑物的给定居住区的卫星图像或航拍图像。机器学习模型是基于该区域停放的汽车的分布而建立的。由此产生的分类模型可以区分低层,中层和高层房屋。波兰一个大城市的三个居民区的航拍图像和WEKA数据挖掘系统证明了该方法的有效性。

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