Semantic segmentation of high-resolution remote sensing images using fully convolutional network with adaptive threshold

Semantic segmentation of high-resolution remote sensing images using fully convolutional network with adaptive threshold

Semantic segmentation is an important method to implement fine-grained semantically understand for high-resolution remote sensing images by dividing images into pixel groupings which can then be labelled and classified. In the field of computer vision (CV), the methods based on fully convolutional n...

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Bibliographic Details
Main Authors: Zhihuan Wu, Yongming Gao, Lei Li, Junshi Xue, Yuntao Li
Format: Article
Language:English
Published: Taylor & Francis Group 2019-04-01
Series:Connection Science
Subjects:
semantic segmentation
remote sensing images
fully convolutional network
class imbalance
adaptive threshold
Online Access:http://dx.doi.org/10.1080/09540091.2018.1510902

Internet

http://dx.doi.org/10.1080/09540091.2018.1510902

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