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pro vyhledávání: '"Pagetti, P."'
The last decade has seen the emergence of a new generation of multi-core in response to advances in machine learning, and in particular Deep Neural Network (DNN) training and inference tasks. These platforms, like the JETSON AGX XAVIER, embed several
Externí odkaz:
http://arxiv.org/abs/2406.14081
Autor:
Cappi, Cyril, Cohen, Noémie, Ducoffe, Mélanie, Gabreau, Christophe, Gardes, Laurent, Gauffriau, Adrien, Ginestet, Jean-Brice, Mamalet, Franck, Mussot, Vincent, Pagetti, Claire, Vigouroux, David
This paper focuses on a Vision-based Landing task and presents the design and the validation of a dataset that would comply with the Operational Design Domain (ODD) of a Machine-Learning (ML) system. Relying on emerging certification standards, we de
Externí odkaz:
http://arxiv.org/abs/2406.14027
Autor:
Belcaid, Mohammed, Bonnafous, Eric, Crison, Louis, Faure, Christophe, Jenn, Eric, Pagetti, Claire
Publikováno v:
12th European Congress on Embedded Real Time Software and Systems, Jun 2024, Toulouse, France
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 objectives and provide sufficient evidences, required by the recommend
Externí odkaz:
http://arxiv.org/abs/2406.12362
Autor:
Lesage, Benjamin, Boniol, Frédéric, Delmas, Kevin, Gauffriau, Adrien, Gonzalez, Alfonso Mascarenas, Pagetti, Claire
The emergence of Deep Neural Network (DNN) and machine learning-based applications paved the way for a new generation of hybrid hardware platforms. Hybrid platforms embed several cores and accelerators in a small package. However, in order to satisfy
Externí odkaz:
http://arxiv.org/abs/2406.12346
Autor:
Cohen, Noémie, Ducoffe, Mélanie, Boumazouza, Ryma, Gabreau, Christophe, Pagetti, Claire, Pucel, Xavier, Galametz, Audrey
We introduce a novel Interval Bound Propagation (IBP) approach for the formal verification of object detection models, specifically targeting the Intersection over Union (IoU) metric. The approach has been implemented in an open source code, named IB
Externí odkaz:
http://arxiv.org/abs/2403.08788
Publikováno v:
12th European Congress on Embedded Real Time Software and Systems (ERTS 2024), Jun 2024, Toulouse, France
Implementing deep neural networks in safety critical systems, in particular in the aeronautical domain, will require to offer adequate specification paradigms to preserve the semantics of the trained model on the final hardware platform. We propose t
Externí odkaz:
http://arxiv.org/abs/2307.12713
Autor:
Ducoffe, Mélanie, Carrere, Maxime, Féliers, Léo, Gauffriau, Adrien, Mussot, Vincent, Pagetti, Claire, Sammour, Thierry
As the interest in autonomous systems continues to grow, one of the major challenges is collecting sufficient and representative real-world data. Despite the strong practical and commercial interest in autonomous landing systems in the aerospace fiel
Externí odkaz:
http://arxiv.org/abs/2304.09938
Autor:
Delseny, Hervé, Gabreau, Christophe, Gauffriau, Adrien, Beaudouin, Bernard, Ponsolle, Ludovic, Alecu, Lucian, Bonnin, Hugues, Beltran, Brice, Duchel, Didier, Ginestet, Jean-Brice, Hervieu, Alexandre, Martinez, Ghilaine, Pasquet, Sylvain, Delmas, Kevin, Pagetti, Claire, Gabriel, Jean-Marc, Chapdelaine, Camille, Picard, Sylvaine, Damour, Mathieu, Cappi, Cyril, Gardès, Laurent, De Grancey, Florence, Jenn, Eric, Lefevre, Baptiste, Flandin, Gregory, Gerchinovitz, Sébastien, Mamalet, Franck, Albore, Alexandre
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 vehicles, recognizing voice, etc. It is also an opportunity to implement
Externí odkaz:
http://arxiv.org/abs/2103.10529
In this paper, we propose a system-level approach for verifying the safety of neural network controlled systems, combining a continuous-time physical system with a discrete-time neural network based controller. We assume a generic model for the contr
Externí odkaz:
http://arxiv.org/abs/2011.05174
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