Building Detection on Aerial Images Using U-NET Neural Networks

Proceedings of the XXth Conference of Open Innovations Association FRUCT

Vladimir Pavlov¹  Leonid Ivanovsky¹  Vladimir Khryashchev¹  Anna Ostrovskaya² 

[1] Demidov Yaroslavl State University, Yaroslavl, Russian Federation;People's Friendship University of Russia (RUDN Un vers ty), Moscow, Russian Federation;

关键词: neural network;    aerial image;    buiding detection;   

DOI  :  

来源: DOAJ

【 摘 要 】

This article presents research results of two convolutional neural networks for building detection on satellite images of Planet database. To analyze the quality of developed algorithms, there was used Sorensen-Dice coefficient of similarity which compares results of algorithms with tagged masks. The masks were generated from json files and sliced on smaller parts together with respective images before the training of algorithms. This approach allows to cope with the problem of segmentation for aerial high-resolution images efficiently and effectively. The problem of building detection on satellite images can be put into practice for urban planning, building control, etc.

【 授权许可】

Unknown