The D-CNN-LSTM Autoencoder method optimizes the anomaly detection rate for all of the anomalies, specifically in the case of low magnitude anomalies, enhancing F1-score up to 18.12% in single types of ...

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’ available ...

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Optimized CNN and CRNN for Advanced Classification and Regression This repository contains the implementation for my third major project, "Optimized CNN and CRNN for Advanced Classification and ...