Deep Convolutional Neural Networks for Semantic Segmentation of Multi-Band Satellite Images

Abstract

Semantic segmentation of images is of increasing interest in the eld of computer vision and machine learning. Accurate and e cient segmentation methods is required for many of todays modern applications. This the- sis provides a review of deep learning methods for semantic segmentation of satellite images. Firstly, we compare di erent state-of-the-art methods. Next, we explore the bene ts of using multiple spectral bands of data as compared to the traditional RGB bands. Finally, a look at future possibil- ities with segmentation using capsule networks.