DSANet: A Deep Supervision-Based Simple Attention Network for Efficient Semantic Segmentation in Remote Sensing Imagery

DSANet: A Deep Supervision-Based Simple Attention Network for Efficient Semantic Segmentation in Remote Sensing Imagery

Semantic segmentation for remote sensing images (RSIs) plays an important role in many applications, such as urban planning, environmental protection, agricultural valuation, and military reconnaissance. With the boom in remote sensing technology, numerous RSIs are generated; this is difficult for c...

Full description

Bibliographic Details
Main Authors: Wenxu Shi, Qingyan Meng, Linlin Zhang, Maofan Zhao, Chen Su, Tamás Jancsó
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Remote Sensing
Subjects:
convolutional neural network (CNN)
deep supervision
lightweight model
remote sensing
semantic segmentation
Online Access:https://www.mdpi.com/2072-4292/14/21/5399

Internet

https://www.mdpi.com/2072-4292/14/21/5399

Similar Items