DeepAI AI Chat
Log In Sign Up

Certification of embedded systems based on Machine Learning: A survey

by   Guillaume Vidot, et al.

Advances in machine learning (ML) open the way to innovating functions in the avionic domain, such as navigation/surveillance assistance (e.g. vision-based navigation, obstacle sensing, virtual sensing), speechto-text applications, autonomous flight, predictive maintenance or cockpit assistance. Current certification standards and practices, which were defined and refined decades over decades with classical programming in mind, do not however support this new development paradigm. This article provides an overview of the main challenges raised by the use ML in the demonstration of compliance with regulation requirements, and a survey of literature relevant to these challenges, with particular focus on the issues of robustness and explainability of ML results.


page 4

page 18


Vision-based Driver Assistance Systems: Survey, Taxonomy and Advances

Vision-based driver assistance systems is one of the rapidly growing res...

Toward Certification of Machine-Learning Systems for Low Criticality Airborne Applications

The exceptional progress in the field of machine learning (ML) in recent...

Machine Learning Sensors

Machine learning sensors represent a paradigm shift for the future of em...

Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots

Machine learning (ML) has become a pervasive tool across computing syste...

A Comprehensive Survey of Machine Learning Based Localization with Wireless Signals

The last few decades have witnessed a growing interest in location-based...

Regularization and False Alarms Quantification: Two Sides of the Explainability Coin

Regularization is a well-established technique in machine learning (ML) ...