Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance
Summary
Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance is a scholarly article[1].
Key Facts
Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance. Retrieved May 24, 2026, from https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-using-deep-transfer-learning-based-on-joint-generalized-sliced-wasserstein-distance
MLA“Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-using-deep-transfer-learning-based-on-joint-generalized-sliced-wasserstein-distance.
BibTeX@misc{4ortxyz_rolling-bearing-fault-diagnosis-using-deep-transfer-learning-based-on-joint-generalized-sliced-wasserstein-distance_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance}}, year = {2026}, url = {https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-using-deep-transfer-learning-based-on-joint-generalized-sliced-wasserstein-distance}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance — https://4ort.xyz/entity/rolling-bearing-fault-diagnosis-using-deep-transfer-learning-based-on-joint-generalized-sliced-wasserstein-distance (retrieved 2026-05-24)
