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’ ...
FenderBender

The ABCs of ADAS

With CCI’s ADAS Essentials course, staff can better educate the customer and insurer on the importance of these safety ...
IEEE

Superpixel-Based Autoencoder-Like Nonnegative Tensor Factorization for Hyperspectral Unmixing

Abstract: Hyperspectral unmixing is significant for advancing remote sensing (RS) applications, aiming at extracting the spectra of pure materials (called endmembers) and obtaining their proportions ...
GitHub

Prometheus Time Series Anomaly Detection with LSTM Autoencoder

This project implements a system for detecting anomalies in time series data collected from Prometheus. It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn ...