Interinstance and Intratemporal Self-Supervised Learning With Few Labeled Data for Fault Diagnosis
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DOI: 10.1109/tii.2022.3183601
Abstract: Recent researches on intelligent fault diagnosis algorithms can achieve great progress. However, considering the practical scenarios, the amount of labeled data is insufficient in face of the difficulty of data annotation, which would raise the… read more here.
Keywords: fault diagnosis; supervised learning; interinstance intratemporal; self supervised ... See more keywords