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ResNet-101 和 RegNetX-400MF 特征融合

ResNet-101 and RegNetX-400MF feature fusion

A machine learning process combining feature extraction from two distinct deep convolutional neural network architectures (ResNet-101 and RegNetX-400MF) followed by data relabeling using the k-means clustering algorithm to classify defects in photovoltaic electroluminescence images. / 一种机器学习过程,结合了来自两种不同深度卷积神经网络架构(ResNet-101 和 RegNetX-400MF)的特征提取,随后使用 k-means 聚类算法进行数据重标记,以对光伏电致发光图像中的缺陷进行分类。

Knowledge type
工艺技术
First proposed or discovered
Proposer
Turkey Farm member
Creator
农场主
Last updated
2026-11-05 22:05:19
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Sub-knowledge points

ResNet-101 feature extractionRegNetX-400MF feature extractionk-means relabeling

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Main parameters and performance indicators

ResNet-101: A deep residual convolutional neural network architecture.RegNetX-400MF: A convolutional neural network architecture.k-means: A clustering algorithm used for relabeling.Photovoltaic electroluminescence: The imaging technique applied.

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ResNet-101 and RegNetX-400MF feature fusion with k-means relabeling for photovoltaic electroluminescence defect classificationOpen source

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automated knowledge publish农场主2026-11-05 22:05:19

Record title: ResNet-101 and RegNetX-400MF feature fusion.