Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey

A McCarthy, E Ghadafi, P Andriotis, P Legg - Journal of Cybersecurity …, 2022 - mdpi.com
Machine learning has become widely adopted as a strategy for dealing with a variety of
cybersecurity issues, ranging from insider threat detection to intrusion and malware …

[HTML][HTML] On-device object detection for more efficient and privacy-compliant visual perception in context-aware systems

I Rodriguez-Conde, C Campos, F Fdez-Riverola - Applied Sciences, 2021 - mdpi.com
Ambient Intelligence (AmI) encompasses technological infrastructures capable of sensing
data from environments and extracting high-level knowledge to detect or recognize users' …

Optimal data reduction of training data in machine learning-based modelling: a multidimensional bin packing approach

J Wibbeke, P Teimourzadeh Baboli, S Rohjans - Energies, 2022 - mdpi.com
In these days, when complex, IT-controlled systems have found their way into many areas,
models and the data on which they are based are playing an increasingly important role …

On-device deep learning inference for system-on-chip (SoC) architectures

T Springer, E Eiroa-Lledo, E Stevens, E Linstead - Electronics, 2021 - mdpi.com
As machine learning becomes ubiquitous, the need to deploy models on real-time,
embedded systems will become increasingly critical. This is especially true for deep learning …

[PDF][PDF] On-Device Deep Learning Inference for System-on-Chip (SoC) Architectures. Electronics 2021, 10, 689

T Springer, E Eiroa-Lledo, E Stevens, E Linstead - 2021 - core.ac.uk
As machine learning becomes ubiquitous, the need to deploy models on real-time,
embedded systems will become increasingly critical. This is especially true for deep learning …