Object-Based Semi-Supervised Spatial Attention Residual UNet for Urban High-Resolution Remote Sensing Image Classification

Object-Based Semi-Supervised Spatial Attention Residual UNet for Urban High-Resolution Remote Sensing Image Classification

Accurate urban land cover information is crucial for effective urban planning and management. While convolutional neural networks (CNNs) demonstrate superior feature learning and prediction capabilities using image-level annotations, the inherent mixed-category nature of input image patches leads to...

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Bibliographic Details
Main Authors: Yuanbing Lu, Huapeng Li, Ce Zhang, Shuqing Zhang
Format: Article
Language:English
Published: MDPI AG 2024-04-01
Series:Remote Sensing
Subjects:
CNN
OBIA
UNet
semi-supervised
semantic segmentation
classification
Online Access:https://www.mdpi.com/2072-4292/16/8/1444

Internet

https://www.mdpi.com/2072-4292/16/8/1444

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