SolarDetector: A Transformer-based Neural Network for the Detection and Masking of Solar Panels
Authors: 
Abdulrahman Salama, Abdeltawab Hendawi, Mohamed Ali, 
Eyhab Al-Masri, Richard Franklin, Anish DeshpandeAuthors Info & Claims
Article No.: 99, Pages 1 - 4
Abstract
As the global transition towards renewable energy sources accelerates, solar power becomes an increasingly important solution. Identifying and understanding the current distribution of solar panel installations is crucial for future planning and decision-making process. This paper introduces SolarDetector, a transformer-based neural network model, which we developed and fine-tuned for the accurate detection of solar panels. It achieves 91.0% mIoU for the task of masking solar panels on SWISSIMAGE dataset.
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Information
Published In
November 2023
686 pages
ISBN:9798400701689
DOI:10.1145/3589132
- General Chairs:
- Maria Luisa Damiani,
- Matthias Renz,
- Program Chairs:
- Ahmed Eldawy,
- Peer Kröger,
- Mario A Nascimento
Copyright © 2023 Owner/Author(s).
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 22 December 2023
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SIGSPATIAL '23
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SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information Systems
November 13 - 16, 2023
Hamburg, Germany
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