CVAug 9, 2018
Object Detection in Satellite Imagery using 2-Step Convolutional Neural Networks
Hiroki Miyamoto, Kazuki Uehara, Masahiro Murakawa, Hidenori Sakanashi, Hirokazu Nosato, Toru Kouyama, Ryosuke Nakamura
arXiv:1808.02996v11 citations
Originality Incremental advance
AI Analysis
This work addresses object detection in satellite imagery, which is incremental as it builds on existing CNN approaches.
The paper tackled object detection in satellite imagery by proposing a two-step convolutional neural network method, achieving higher accuracy than previous methods for identifying golf courses.
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.