DFD augments scarce labeled vibration data for CNN training via pseudo-labels from feature-selected SVMs on STFT spectrograms, outperforming standalone SVMs and vanilla CNNs on two datasets.
Research of facial beauty prediction based on deep convolutional features using double activation layer
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Deep Fault Diagnosis for Rotating Machinery with Scarce Labeled Samples
DFD augments scarce labeled vibration data for CNN training via pseudo-labels from feature-selected SVMs on STFT spectrograms, outperforming standalone SVMs and vanilla CNNs on two datasets.