SDSNet: Building Extraction in High-Resolution Remote Sensing Images Using a Deep Convolutional Network with Cross-Layer Feature Information Interaction Filtering
Building extraction refers to the automatic identification and separation of buildings from the background in remote sensing images. It plays a significant role in urban planning, land management, and disaster monitoring. Deep-learning methods have shown advantages in building extraction, but they s...
Main Authors: | Xudong Wang, Mingliang Tian, Zhijun Zhang, Kang He, Sheng Wang, Yan Liu, Yusen Dong |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-12-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/16/1/169 |
Similar Items
-
Fine crop classification in high resolution remote sensing based on deep learning
by: Tingyu Lu, et al.
Published: (2022-10-01) -
Complex Mountain Road Extraction in High-Resolution Remote Sensing Images via a Light Roadformer and a New Benchmark
by: Xinyu Zhang, et al.
Published: (2022-09-01) -
Gaussian Dynamic Convolution for Semantic Segmentation in Remote Sensing Images
by: Mingzhe Feng, et al.
Published: (2022-11-01) -
Edge Guidance Network for Semantic Segmentation of High-Resolution Remote Sensing Images
by: Yue Ni, et al.
Published: (2023-01-01) -
Scale-Aware Neural Network for Semantic Segmentation of Multi-Resolution Remote Sensing Images
by: Libo Wang, et al.
Published: (2021-12-01)