High-Precision Defect Detection in Solar Cells Using YOLOv10 Deep Learning Model

High-Precision Defect Detection in Solar Cells Using YOLOv10 Deep Learning Model

This study presents an advanced defect detection approach for solar cells using the YOLOv10 deep learning model. Leveraging a comprehensive dataset of 10,500 solar cell images annotated with 12 distinct defect types, our model integrates Compact Inverted Blocks (CIBs) and Partial Self-Attention (PSA...

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Bibliographic Details
Main Authors: Lotfi Aktouf, Yathin Shivanna, Mahmoud Dhimish
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Solar
Subjects:
YOLOv10
object detection
deep learning
photovoltaic manufacturing
Online Access:https://www.mdpi.com/2673-9941/4/4/30
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