IEEE

Masked Autoencoder via End-to-End Zero-Shot Learning for Fault Diagnosis of Unseen Classes

Abstract: This study confronts a demanding fault diagnosis task where no sensor signals from the target faults can be utilized for model training. Considering semantic descriptions of the target (or ...
IEEE

Dynamic Semantic Compression for CNN Inference in Multi-Access Edge Computing: A Graph Reinforcement Learning-Based Autoencoder

Abstract: This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and edge servers’ ...