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Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey
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 …
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
Ambient Intelligence (AmI) encompasses technological infrastructures capable of sensing
data from environments and extracting high-level knowledge to detect or recognize users' …
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
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 …
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
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 …
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 …
embedded systems will become increasingly critical. This is especially true for deep learning …