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Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs
Research article (IEEE Access, 2023) · cited 61× · AI/ML
Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs
Summary
Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs is a scholarly article[1].
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Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs. Retrieved May 24, 2026, from https://4ort.xyz/entity/improving-bearing-fault-identification-by-using-novel-hybrid-involution-convolution-feature-extraction-with-adversarial-
MLA“Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/improving-bearing-fault-identification-by-using-novel-hybrid-involution-convolution-feature-extraction-with-adversarial-.
BibTeX@misc{4ortxyz_improving-bearing-fault-identification-by-using-novel-hybrid-involution-convolution-feature-extraction-with-adversarial-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs}}, year = {2026}, url = {https://4ort.xyz/entity/improving-bearing-fault-identification-by-using-novel-hybrid-involution-convolution-feature-extraction-with-adversarial-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs — https://4ort.xyz/entity/improving-bearing-fault-identification-by-using-novel-hybrid-involution-convolution-feature-extraction-with-adversarial- (retrieved 2026-05-24)
