Dust InSMS: Intelligent soiling measurement system for dust detection on solar mirrors using computer vision methods-Reference-Cited by-同舟云学术

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Dust InSMS: Intelligent soiling measurement system for dust detection on solar mirrors using computer vision methods

Published:2023-01 Issue: Volume:211 Page:118646
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

El Ydrissi Massaab,Ghennioui Hicham,Ghali Bennouna El,Alae Azouzoute,Abraim Mounir,Taabane Ibrahim,Farid Abdi

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference59 articles.

1. Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer deep learning;Akram;Solar Energy,2020

2. Al-Saffar, A. A. M., Tao, H., & Talab, M. A. (2017). Review of deep convolution neural network in image classification. 26–31. http://dx.doi.org/10.1109/ICRAMET.2017.8253139.

3. Medical image analysis using convolutional neural networks: A review;Anwar;Journal of Medical Systems,2018

4. Soiling loss of solar glass and mirror samples in the region with arid climate;Azouzoute;Energy Reports,2020

5. Developing a cleaning strategy for hybrid solar plants PV/CSP: Case study for semi-arid climate;Azouzoute;Energy,2021

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1. CASolarNet: Channel Attention EfficientNet-based Model for Solar Panel Dust Detection;2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA);2024-08-06

2. Influence of environmental dust accumulation on the performance and economics of solar energy systems: A comprehensive review;Cleaner Energy Systems;2024-08

3. Meta-learning with hypernetworks: Cost-effective fault detection in Parabolic Trough plants;Engineering Applications of Artificial Intelligence;2024-07

4. Measuring Ball Joint Faults in Parabolic-Trough Solar Plants with Data Augmentation and Deep Learning;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. A Survey of Photovoltaic Panel Overlay and Fault Detection Methods;Energies;2024-02-09

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