Object Detection in Satellite Imagery using 2-Step Convolutional Neural Networks

TL;DR

This paper introduces a two-step CNN approach for object detection in satellite images, achieving higher accuracy than previous methods by focusing on golf course detection.

Contribution

The paper proposes a novel combination of two CNNs for improved object detection accuracy in satellite imagery.

Findings

Higher detection accuracy than previous methods

Effective detection of golf courses in satellite images

Demonstrated high precision and recall

Abstract

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.