Classification of high resolution satellite images using improved U-Net - Wang, Yong; Zhang, Dongfang; Dai, Guangming (Zielona Góra: Uniwersytet Zielonogórski)
Satellite image classification is essential for many socio-economic and environmental applications of geographic information systems, including urban and regional planning, conservation and management of natural resources, etc. In this paper, we propose a deep learning architecture to perform the pixel-level understanding of high spatial resolution satellite images and apply it to image classification tasks.
Keywords: satellite image classification; deep learning; U-Net; spatial pyramid pooling