Fault Classification based on Deep Learning for Photovoltaic Systems-Reference-Cited by-同舟云学术

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Fault Classification based on Deep Learning for Photovoltaic Systems

Published:2024-03-15 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT)
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Author:

Kelin A R Darshika¹,Sudhakar K²,Surekha Pothireddy³,Palanivel R⁴,Al-Jawahry Hassan M⁵

Affiliation:

1. Karunya Institute of Technology and Sciences,Data Science and Cyber Security,Karunya Nagar, Coimbatore,India

2. Mallareddy Engineering College for Women (Autonomous),Department Electronics and Communication Engineering,Hyderabad,Telangana,India

3. GRIET,Department of Computer Science and Engineering,Hyderabad,Telangana,India

4. Nitte Meenakshi Institute of Technology,Department of AI and DS,Bengaluru,India

5. The Islamic university,Najaf,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10515307/10515308/10515564.pdf?arnumber=10515564

Reference15 articles.

1. One-Class Machine Learning Classifiers-Based Multivariate Feature Extraction for Grid-Connected PV Systems Monitoring under Irradiance Variations

2. Adversarial Unsupervised Domain Adaptation for Hand Gesture Recognition Using Thermal Images

3. Visual fault detection in photovoltaic modules using decision tree algorithms with deep learning features

4. Margin-based Adversarial Learning for Domain Generalization;Dayal

5. Statistical Analysis and Development of an Ensemble-Based Machine Learning Model for Photovoltaic Fault Detection

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