Automated Rooftop Solar Panel Detection Through Convolutional Neural Networks
Transforming the global energy sector from fossil-fuel based to renewable energy sources is crucial to limiting global warming and achieving climate neutrality. The decentralized nature of the renewable energy system allows private households to deploy photovoltaic systems on their rooftops. However...
Saved in:
| Main Authors: | Simon Pena Pereira, Azarakhsh Rafiee, Stef Lhermitte |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Canadian Journal of Remote Sensing |
| Online Access: | http://dx.doi.org/10.1080/07038992.2024.2363236 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Environmental Fault Diagnosis of Solar Panels Using Solar Thermal Images in Multiple Convolutional Neural Networks
by: Tamilselvi Selvaraj, et al.
Published: (2022-01-01) -
Automated Detection of Microseismic Arrival Based on Convolutional Neural Networks
by: Weijian Liu, et al.
Published: (2022-01-01) -
Automated Malaria Detection Using Convolutional Neural Networks and Machine Learning
by: Adel Lateef Albukhnefis
Published: (2024-12-01) -
Improving the resolution of solar energy potential maps derived from global DSMs for rooftop solar panel placement using deep learning
by: Maryam Hosseini, et al.
Published: (2025-01-01) -
Automated Detection of Spine Deformities: Advancing Orthopedic Care with Convolutional Neural Networks
by: Deepesh Pratap, et al.
Published: (2024-12-01)