Don't Just Impute, Detect: Task-Aware Diffusion Pipelines for Edge Anomaly Detection
arXiv:2610.40732v1 Announce Type: new Abstract: Industrial Internet of Things (IIoT) edge pipelines routinely lose contiguous blocks of multi-sensor data to network dropouts and hardware faults. The standard remedy is a disjointed "impute-then-detect" pipeline whose imputer is trained only for Mean Squared Error (MSE). Such an imputer fills a missing block with the most probable normal pattern: a partially observed anomaly is smoothed back toward normality, and boundary artifacts on normal data raise false alarms. We call this imputation bias and propose the Task-Aware Diffusion Refiner (TADR)
阅读原文 · arXiv 机器学习本文由 SoccerDream AI 自动聚合索引，内容版权归原作者与 arXiv 机器学习 所有。
本站仅作技术动态聚合，不构成任何形式的建议。
本站仅作技术动态聚合，不构成任何形式的建议。