[HTML][HTML] Emerging information and communication technologies for smart energy systems and renewable transition

N Zhao, H Zhang, X Yang, J Yan, F You - Advances in Applied Energy, 2023‏ - Elsevier
Since the energy sector is the dominant contributor to global greenhouse gas emissions, the
decarbonization of energy systems is crucial for climate change mitigation. Two major …

[HTML][HTML] GeoAI for detection of solar photovoltaic installations in the Netherlands

BB Kausika, D Nijmeijer, I Reimerink, P Brouwer… - Energy and AI, 2021‏ - Elsevier
National map** agencies are responsible for creating and maintaining country wide
geospatial datasets that are highly accurate and homogenous. The Netherlands' Cadastre …

[HTML][HTML] Partial linear NMF-based unmixing methods for detection and area estimation of photovoltaic panels in urban hyperspectral remote sensing data

MS Karoui, FZ Benhalouche, Y Deville, K Djerriri… - Remote Sensing, 2019‏ - mdpi.com
High-spectral-resolution hyperspectral data are acquired by sensors that gather images from
hundreds of narrow and contiguous bands of the electromagnetic spectrum. These data offer …

Detecting faulty solar panels based on thermal image processing

SW Lee, KE An, BD Jeon, KY Cho… - 2018 IEEE …, 2018‏ - ieeexplore.ieee.org
Recently, the solar power generation has attracted much attention and market is growing.
Although it is more common than in the past, there is not enough specialist for maintenance …

[HTML][HTML] Automatic boundary extraction for photovoltaic plants using the deep learning U-net model

A Pérez-González, Á Jaramillo-Duque… - Applied Sciences, 2021‏ - mdpi.com
Nowadays, the world is in a transition towards renewable energy solar being one of the most
promising sources used today. However, Solar Photovoltaic (PV) systems present great …

Automated rooftop solar panel detection through Convolutional Neural Networks

S Pena Pereira, A Rafiee… - Canadian Journal of …, 2024‏ - Taylor & Francis
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 …

[PDF][PDF] Comparing boosted cascades to deep learning architectures for fast and robust coconut tree detection in aerial images

S Puttemans, K Van Beeck… - Proceedings of the 13th …, 2018‏ - lirias.kuleuven.be
Object detection using a boosted cascade of weak classifiers is a principle that has been
used in a variety of applications, ranging from pedestrian detection to fruit counting in …

Detection and area estimation for photovoltaic panels in urban hyperspectral remote sensing data by an original NMF-based unmixing method

MS Karoui, F zohra Benhalouche… - IGARSS 2018-2018 …, 2018‏ - ieeexplore.ieee.org
Hyperspectral remote sensing data offer unique opportunities for the characterization of land
surface in urban areas. However, no hyperspectral-unmixing based studies have been …

Software for roof defects recognition on aerial photographs

D Yudin, A Naumov, A Dolzhenko… - Journal of Physics …, 2018‏ - iopscience.iop.org
The article presents information on software for roof defects recognition on aerial
photographs, made with air drones. An areal image segmentation mechanism is described …

Monitoring spatial sustainable development: semi-automated analysis of satellite and aerial images for energy transition and sustainability indicators

T De Jong, S Bromuri, X Chang… - arxiv preprint arxiv …, 2020‏ - arxiv.org
This report presents the results of the DeepSolaris project that was carried out under the
ESS action'Merging Geostatistics and Geospatial Information in Member States'. During the …