Automated Rooftop Solar Panel Detection Through Convolutional Neural Networks

Author:

Pena Pereira Simon1ORCID,Rafiee Azarakhsh1ORCID,Lhermitte Stef23ORCID

Affiliation:

1. Geo-Database Management Center, Delft University of Technology, Delft, The Netherlands

2. Department Earth & Environmental Sciences, KU Leuven, Leuven, Belgium

3. Department Geoscience & Remote Sensing, Delft University of Technology, Delft, The Netherlands

Publisher

Informa UK Limited

Reference29 articles.

1. Infrared imaging of photovoltaic modules: a review of the state of the art and future challenges facing gigawatt photovoltaic power stations

2. Deep learning in the built environment: automatic detection of rooftop solar panels using Convolutional Neural Networks

3. ClimateWatch. 2022. “Climate watch historical country greenhouse gas emissions data.” Last modified January 04 2023 https://www.climatewatchdata.org/ghg-emissions? end_year=2019&start_year=1990.

4. Remote Sensing for Monitoring Photovoltaic Solar Plants in Brazil Using Deep Semantic Segmentation

5. De Jong T. Bromuri S. Chang X. Debusschere M. Rosenski N. Schartner C. Strauch K. Boehmer M. and Curier L. 2020. “Monitoring spatial sustainable development: Semiautomated analysis of satellite and aerial images for energy transition and sustainability indicators.” CoRR abs/2009.05738.

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