Abstract: Unsupervised time-series clustering and timely anomaly detection are critical in manufacturing, where large volumes of streaming data are collected but labeled information is scarce. These ...

Abstract: This paper introduces an enhanced approach for deploying deep learning models on resource-constrained IoT devices by combining model partitioning, autoencoder-based compression, quantization ...