A transfer convolutional neural network for fault diagnosis based on ResNet-50
With the rapid development of smart manufacturing, data-driven fault diagnosis has attracted increasing attentions. As one of the most popular methods applied in fault diagnosis, deep learning (DL) has achieved remarkable results. However, due to the fact that the volume of labeled samples is small...
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Veröffentlicht in: | Neural computing & applications 2020-05, Vol.32 (10), p.6111-6124 |
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