This paper presents an efficient object detection method from satellite imagery. Among a number of machine learning algorithms, we proposed a combination of two convolutional neural networks (CNN) aimed at high precision and high recall, respectively. We validated our models using golf courses as target objects. The proposed deep learning method demonstrated higher accuracy than previous object identification methods.
@article{arxiv.1808.02996,
title = {Object Detection in Satellite Imagery using 2-Step Convolutional Neural Networks},
author = {Hiroki Miyamoto and Kazuki Uehara and Masahiro Murakawa and Hidenori Sakanashi and Hirokazu Nosato and Toru Kouyama and Ryosuke Nakamura},
journal= {arXiv preprint arXiv:1808.02996},
year = {2018}
}