5 papers
A Convolutional Layer Activation Dimensionality Reduction for Out-of-Distribution and Adversarial Attack Detection Methods
Leandro de Souza Rosa, Lorenzo Capelli, Clara Nunes Barrancos +2
Despite the success of convolutional neural networks in image classification tasks and their general application in multi-modal models, their susceptibility to out-of-distribution…
On-board Telemetry Monitoring in Autonomous Satellites: Challenges and Opportunities
Lorenzo Capelli, Leandro de Souza Rosa, Maurizio De Tommasi +8
The increasing autonomy of spacecraft demands fault-detection systems that are both reliable and explainable. This work addresses eXplainable Artificial Intelligence for onboard Fa…
Multi-Layer Confidence Scoring for Detection of Out-of-Distribution Samples, Adversarial Attacks, and In-Distribution Misclassifications
Lorenzo Capelli, Leandro de Souza Rosa, Gianluca Setti +2
The recent explosive growth in Deep Neural Networks applications raises concerns about the black-box usage of such models, with limited trasparency and trustworthiness in high-stak…
RDD: Pareto Analysis of the Rate-Distortion-Distinguishability Trade-off
Andriy Enttsel, Alex Marchioni, Andrea Zanellini +3
Extensive monitoring systems generate data that is usually compressed for network transmission. This compressed data might then be processed in the cloud for tasks such as anomaly…
Goal-Oriented Joint Source-Channel Coding: Distortion-Classification-Power Trade-off
Andriy Enttsel, Weichen Wang, Mauro Mangia +2
Joint source-channel coding is a compelling paradigm when low-latency and low-complexity communication is required. This work proposes a theoretical framework that integrates class…