A Stacked Fully Convolutional Networks with Feature Alignment Framework for Multi-Label Land-cover Segmentation

A Stacked Fully Convolutional Networks with Feature Alignment Framework for Multi-Label Land-cover Segmentation

Applying deep-learning methods, especially fully convolutional networks (FCNs), has become a popular option for land-cover classification or segmentation in remote sensing. Compared with traditional solutions, these approaches have shown promising generalization capabilities and precision levels in...

Full description

Bibliographic Details
Main Authors: Guangming Wu, Yimin Guo, Xiaoya Song, Zhiling Guo, Haoran Zhang, Xiaodan Shi, Ryosuke Shibasaki, Xiaowei Shao
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Remote Sensing
Subjects:
land-cover classification
image segmentation
ensemble learing
feature alignment
fully convolutional networks
Online Access:https://www.mdpi.com/2072-4292/11/9/1051

Internet

https://www.mdpi.com/2072-4292/11/9/1051

Similar Items