標題: Learning with Detail and Morphological Refinement for Satellite Image Analysis based on Convolutional Neural Network
作者: Lin, Guan-Ting
Yang, Yung-I
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
公開日期: 1-Jan-2018
摘要: we present a multiple stages way to analyze the content of satellite images. Our methodology is divided into three major steps. First, Convolutional Neural Networks (CNNs) for semantic segmentation between buildings and nature scene. Then, the output semantic image would be refined in morphology way. In the last stage, Depth-First Search (DFS) algorithm is used for buildings counting. The experimental results show that refined images have smother boundaries. Base on the output images, we can count buildings using DFS algorithm accurately by refined image.
URI: http://hdl.handle.net/11536/150942
ISSN: 2381-5779
期刊: 2018 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS-TAIWAN (ICCE-TW)
Appears in Collections:Conferences Paper