CSPPNet: A Convolution and State-Space-Based Photovoltaic Panel Extraction Network Using Gaofen-2 High-Resolution Imagery
With the rapid development of photovoltaic (PV) industry, it is crucial to accurately identify PV panels using remote sensing data. However, the existing methods still face problems, such as difficulty in distinguishing PV panels from easily confused ground objects, such as dark buildings, roads, an...
Saved in:
| Main Authors: | Wenqing Liu, Hongtao Huo, Luyan Ji, Yongchao Zhao, Xiaowen Liu, Jialei Xie |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10892037/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Impact assessment of photovoltaic panels with life cycle analysis techniques
by: Nikolaos Skarkos, et al.
Published: (2025-12-01) -
Thermal Analysis of Photovoltaic Panel Cooled by Electrospray Using Different Fluids
by: Ahmet Öztürk, et al.
Published: (2024-10-01) -
From Waste to Resource: Exploring the Current Challenges and Future Directions of Photovoltaic Solar Cell Recycling
by: Ghadeer Badran, et al.
Published: (2025-02-01) -
Some aspects of positioning photo voltaic panels in agrovoltaics applications
by: Kjosevski Stevan, et al.
Published: (2025-01-01) -
Temperature and Solar Radiation Effects on Photovoltaic Panel Power
by: Akif Karafil, et al.
Published: (2016-11-01)