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The prevailing methodology in data-driven fault detection leverages synthetic data for training neural networks. However, it grapples with challenges when it comes to generalization in surveys exhibiting complex structures. To enhance the generalizat
Externí odkaz:
http://arxiv.org/abs/2309.02930
