18 citations · 21 across the 4 of their papers we have counts for
5 papers
Certified ML Object Detection for Surveillance Missions
Mohammed Belcaid, Eric Bonnafous, Louis Crison +3
In this paper, we present a development process of a drone detection system involving a machine learning object detection component. The purpose is to reach acceptable performance…
White Paper Machine Learning in Certified Systems
Hervé Delseny, Christophe Gabreau, Adrien Gauffriau +25
Machine Learning (ML) seems to be one of the most promising solution to automate partially or completely some of the complex tasks currently realized by humans, such as driving veh…
Dataset Definition Standard (DDS)
Cyril Cappi, Camille Chapdelaine, Laurent Gardes +4
This document gives a set of recommendations to build and manipulate the datasets used to develop and/or validate machine learning models such as deep neural networks. This documen…
Ensuring Dataset Quality for Machine Learning Certification
Sylvaine Picard, Camille Chapdelaine, Cyril Cappi +4
In this paper, we address the problem of dataset quality in the context of Machine Learning (ML)-based critical systems. We briefly analyse the applicability of some existing stand…
From Event-B to Verified C via HLL
Ning Ge, Arnaud Dieumegard, Eric Jenn +1
This work addresses the correct translation of an Event-B model to C code via an intermediate formal language, HLL. The proof of correctness follows two main steps. First, the fina…