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Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition
Research article (Journal of Mechanical Engineering Automation and Control Systems, 2021) · cited 10× · AI/ML
Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition
Summary
Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition is a scholarly article[1].
Key Facts
Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition. Retrieved May 24, 2026, from https://4ort.xyz/entity/identification-of-shallow-cracks-in-rotating-systems-by-utilizing-convolutional-neural-networks-and-persistence-spectrum
MLA“Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/identification-of-shallow-cracks-in-rotating-systems-by-utilizing-convolutional-neural-networks-and-persistence-spectrum.
BibTeX@misc{4ortxyz_identification-of-shallow-cracks-in-rotating-systems-by-utilizing-convolutional-neural-networks-and-persistence-spectrum_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition}}, year = {2026}, url = {https://4ort.xyz/entity/identification-of-shallow-cracks-in-rotating-systems-by-utilizing-convolutional-neural-networks-and-persistence-spectrum}, note = {Accessed: 2026-05-24}}
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