An Infrared and Visible Image Fusion Algorithm Based on ResNet152

Heng, 李恒 Li; Liming, 张黎明 Zhang; Meirong, 蒋美容 Jiang; Yulong, 李玉龙 Li

doi:10.3788/lop57.081013

Laser Optoelectron. Prog.

2020

DOI: 10.3788/lop57.081013

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An Infrared and Visible Image Fusion Algorithm Based on ResNet152

李恒 Li Heng¹,

张黎明 Zhang Liming²,

蒋美容 Jiang Meirong³

et al.

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Deep-Learning-Based Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images

Wang

Sun

et al. 2022

Sensors

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Photovoltaic (PV) cell defect detection has become a prominent problem in the development of the PV industry; however, the entire industry lacks effective technical means. In this paper, we propose a deep-learning-based defect detection method for photovoltaic cells, which addresses two technical challenges: (1) to propose a method for data enhancement and category weight assignment, which effectively mitigates the impact of the problem of scant data and data imbalance on model performance; (2) to propose a feature fusion method based on ResNet152–Xception. A coordinate attention (CA) mechanism is incorporated into the feature map to enhance the feature extraction capability of the existing model. The proposed model was conducted on two global publicly available PV-defective electroluminescence (EL) image datasets, and using CNN, Vgg16, MobileNetV2, InceptionV3, DenseNet121, ResNet152, Xception and InceptionResNetV2 as comparative benchmarks, it was evaluated that several metrics were significantly improved. In addition, the accuracy reached 96.17% in the binary classification task of identifying the presence or absence of defects and 92.13% in the multiclassification task of identifying different defect types. The numerical experimental results show that the proposed deep-learning-based defect detection method for PV cells can automatically perform efficient and accurate defect detection using EL images.

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Deep-Learning-Based Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images

Wang

Sun

et al. 2022

Sensors

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基于引导滤波与双树复小波变换的红外与可见光图像融合

Jiang Mai,

Sha Guijun,

Li Ning

2023

激光与光电子学进展

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An Infrared and Visible Image Fusion Algorithm Based on ResNet152

Cited by 2 publications

References 0 publications

Deep-Learning-Based Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images

Deep-Learning-Based Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images

基于引导滤波与双树复小波变换的红外与可见光图像融合

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