Deep learning: systematic review, models, challenges, and research directions

T Talaei Khoei, H Ould Slimane… - Neural Computing and …, 2023‏ - Springer
The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …

Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects

NE Benti, MD Chaka, AG Semie - Sustainability, 2023‏ - mdpi.com
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …

Machine learning and deep learning in energy systems: A review

MM Forootan, I Larki, R Zahedi, A Ahmadi - Sustainability, 2022‏ - mdpi.com
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …

Improved YOLOv8-GD deep learning model for defect detection in electroluminescence images of solar photovoltaic modules

Y Cao, D Pang, Q Zhao, Y Yan, Y Jiang, C Tian… - … Applications of Artificial …, 2024‏ - Elsevier
Photovoltaic defect detection is an essential aspect of research on building-distributed
photovoltaic systems. Existing photovoltaic defect detection models based on deep learning …

Infrared machine vision and infrared thermography with deep learning: A review

Y He, B Deng, H Wang, L Cheng, K Zhou, S Cai… - Infrared physics & …, 2021‏ - Elsevier
Infrared imaging-based machine vision (IRMV) is the technology used to automatically
inspect, detect, and analyse infrared images (or videos) obtained by recording the intensity …

Brain tumor/mass classification framework using magnetic-resonance-imaging-based isolated and developed transfer deep-learning model

MF Alanazi, MU Ali, SJ Hussain, A Zafar, M Mohatram… - Sensors, 2022‏ - mdpi.com
With the advancement in technology, machine learning can be applied to diagnose the
mass/tumor in the brain using magnetic resonance imaging (MRI). This work proposes a …

Fault diagnosis of photovoltaic modules using deep neural networks and infrared images under Algerian climatic conditions

N Kellil, A Aissat, A Mellit - Energy, 2023‏ - Elsevier
The number of decentralized photovoltaic (PV) systems generating electricity has increased
significantly, and its monitoring and maintenance has become a challenge in terms of …

Artificial intelligence and internet of things to improve efficacy of diagnosis and remote sensing of solar photovoltaic systems: Challenges, recommendations and future …

A Mellit, S Kalogirou - Renewable and Sustainable Energy Reviews, 2021‏ - Elsevier
Currently, a huge number of photovoltaic plants have been installed worldwide and these
plants should be carefully protected and supervised continually in order to be safe and …

Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review

B Li, C Delpha, D Diallo, A Migan-Dubois - Renewable and Sustainable …, 2021‏ - Elsevier
The rapid development of photovoltaic (PV) technology and the growing number and size of
PV power plants require increasingly efficient and intelligent health monitoring strategies to …

Failures of Photovoltaic modules and their Detection: A Review

MW Akram, G Li, Y **, X Chen - Applied Energy, 2022‏ - Elsevier
Photovoltaic (PV) has emerged as a promising and phenomenal renewable energy
technology in the recent past and the PV market has developed at an exponential rate …