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InfoResearchPeer-reviewed
DeepFilter: A Transformer-Style Framework for Accurate and Efficient Process Monitoring
- Published
- Record updated
Summary
DeepFilter modifies the Transformer architecture for industrial process monitoring by replacing the self-attention layer with an efficient filtering layer. The authors argue that canonical self-attention struggles with discriminative patterns in monitoring logs and has quadratic computational complexity, while the filtering layer captures long-term patterns at reduced cost. Experiments on real-world process monitoring datasets reportedly show better accuracy and efficiency than existing state-of-the-art models.