Anomaly detection is critically important in ensuring the required stability and reliability of industrial equipment. Conventional methods for it typically assume the availability of sufficient samples from both normal and faulty operating conditions. In practice, however, real-world industrial scenarios rarely provide...
Transformer with Variational AutoEncoder is presented, a framework that combines a dual-embedding representation pipeline, a Transformer encoder for long-range dependency modeling, and VAE-based latent regularization of encoded features to provide an effective and robust solution for long-term time-series anomaly detec...
Xian-Kun Shi, Yi-Bo Li, Zi-Qi Wang et al.· CAAI Artificial Intelligence...· 0 citations
This survey focuses on how cloud-side large models and edge-side small models share, update, and coordinate knowledge and identifies open challenges for trustworthy, sustainable, and self-evolving cloud–edge collaborative intelligence.
Yaxi Yang, Jing-Ye Bi, Haitao Yuan et al.· Journal of Artificial Intell...· 0 citations
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