空中和卫星照片中的建筑物识别

Дмитрий Булатицкий, D. Bulatitskiy, Александр Буйвал, Aleksandr Buyval, Михаил Гавриленков, Mikhail Gavrilenkov
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引用次数: 1

摘要

本文研究了航空照片和卫星照片中的建筑物识别算法。利用卷积人工神经网络解决图像分割问题。考虑了两种人工神经网络结构之间的选择。介绍了基于卷积神经网络的建筑识别软件的开发。描述了该软件综合体的体系结构、其构建的一些特点以及与云地理信息平台的交互。介绍了所开发的软件在图像中建筑物识别中的应用。分析了利用所开发的软件对不同分辨率和不同类型的建筑物图像进行建筑物识别的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building Recognition in Air and Satellite Photos
The paper deals with the algorithms of building recognition in air and satellite photos. The use of convolutional artificial neural networks to solve the problem of image segmentation is substantiated. The choice between two architectures of artificial neural networks is considered. The development of software implementing building recognition based on convolutional neural networks is described. The architecture of the software complex, some features of its construction and interaction with the cloud geo-information platform in which it functions are described. The application of the developed software for the recognition of buildings in images is described. The results of experiments on building recognition in pictures of various resolutions and types of buildings using the developed software are analysed.
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