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Deep learning: systematic review, models, challenges, and research directions
The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …
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
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) …
renewable energy generation using machine learning (ML) and deep learning (DL) …
Machine learning and deep learning in energy systems: A review
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 …
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 …
photovoltaic systems. Existing photovoltaic defect detection models based on deep learning …
Infrared machine vision and infrared thermography with deep learning: A review
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 …
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
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 …
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
The number of decentralized photovoltaic (PV) systems generating electricity has increased
significantly, and its monitoring and maintenance has become a challenge in terms of …
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 …
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 …
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
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 …
PV power plants require increasingly efficient and intelligent health monitoring strategies to …
Failures of Photovoltaic modules and their Detection: A Review
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 …
technology in the recent past and the PV market has developed at an exponential rate …