Skip to main content
Ir a la página de inicio de la Comisión Europea (se abrirá en una nueva ventana)
español español
CORDIS - Resultados de investigaciones de la UE
CORDIS

AI-based CCAM: Trustworthy, Explainable, and Accountable

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Methodology for explainable, trustworthy and human centric AI based system and function development (se abrirá en una nueva ventana)

[T1.1-3] This deliverable will materialize the AITHENA methodology into a reference report to include definition of KPI related to trusted AI features (see GO-8).

Report on initial AI algorithm development (se abrirá en una nueva ventana)

[T3.2-5] This report covers the initial AI algorithm developments including their initial feature validation according to the specified requirements and specifications.

Report on initial use case evaluation (se abrirá en una nueva ventana)

[T5.2-4] This report covers the initial demonstrator validation and evaluation of the demonstrators against the specified requirements and specifications.

Privacy-preserving methods (se abrirá en una nueva ventana)

[T2.3] This deliverable will report the designed privacy-preserving methods for application of GDPR-compliant ML.

Life-cycle management framework for ML models (se abrirá en una nueva ventana)

[T3.1] This report covers the designed AI-framework used for the development and life-cycle assessment of individual ML algorithms.

User group needs report and technical use case definition (se abrirá en una nueva ventana)

[T1.4] This deliverable reports the action taken to identify user groups and gather from them requirements to detail the AITHENA use cases

Initial communication, dissemination and standardisation plan (se abrirá en una nueva ventana)

T613 Initial strategy for AITHENA based on an initial market and stakeholder analysis

Testing and evaluation methodology for AI-driven CCAM systems (se abrirá en una nueva ventana)

[T5.1] This report outlines a joint testing and evaluation methodology for AI-driven CCAM systems to be applied in the corresponding use cases of task 5.2 to task 5.4.

Updated communication, dissemination and standardisation plan (se abrirá en una nueva ventana)

Update of the communication, dissemination and standardisation plan

ML DevOps-oriented data life-cycle governance and provenance framework (se abrirá en una nueva ventana)

[T2.2] This deliverable will report RTD activities related to ML DevOps tools for data governance and provenance.

Publicaciones

Runtime Safety Assurance of Autonomous Vehicles (se abrirá en una nueva ventana)

Autores: A. Forrai (Siemens Industry Software Netherlands B.V.), V. Neelgundmath, K.K. Unni, I. Barosan (Eindhoven University of Technology)
Publicado en: Proceedings: 2023 7th International Conference on System Reliability and Safety (ICSRS), 2023, ISSN 1272-4017
Editor: Zenodo
DOI: 10.5281/zenodo.12724017

Digital twin for synthetic data generation – application for automated driving systems (se abrirá en una nueva ventana)

Autores: Hassan Hotait (HAN – University of Applied Sciences), Alexandru Forrai (Siemens Industry Software Netherlands B.V.)
Publicado en: Product solutions paper: 22nd Driving Simulation & Virtual Reality Conference, 2023, ISSN 1272-3883
Editor: Zenodo
DOI: 10.5281/zenodo.12723882

An Evaluation of Time-triggered Scheduling in the Linux Kernel (se abrirá en una nueva ventana)

Autores: Paraskevas Karachatzis, Jan Ruh, Silviu S. Craciunas (TTTech Computertechnik AG, Vienna, Austria)
Publicado en: RTNS '23: Proceedings of the 31st International Conference on Real-Time Networks and Systems, 2023, ISBN 9781450399838
Editor: ACM
DOI: 10.1145/3575757.3593660

Explainable Multi-Camera 3D Object Detection with Transformer-Based Saliency Maps (se abrirá en una nueva ventana)

Autores: Beemelmanns, Till; Zahr, Wassim; Eckstein, Lutz
Publicado en: Machine Learning for Autonomous Driving Workshop 2023 (NeurIPS), 2023, ISSN 2331-8422
Editor: ML4AD/arXiv
DOI: 10.48550/arxiv.2312.14606

Trustworthiness Assurance Assessment for High-Risk AI-Based Systems (se abrirá en una nueva ventana)

Autores: Georg Stettinger (Infineon Technologies AG); Patrick Weissensteiner (Virtual Vehicle Research GmbH); Siddartha Khastgir (International Manufacturing Centre, The University of Warwick)
Publicado en: IEEE Access, Edición Volume: 12, 2024, ISSN 2169-3536
Editor: IEEE
DOI: 10.1109/ACCESS.2024.3364387

WebLabel: OpenLABEL-compliant multi-sensor labelling (se abrirá en una nueva ventana)

Autores: Itziar Urbieta, Andoni Mujika, Gonzalo Piérola, Eider Irigoyen, Marcos Nieto, Estibaliz Loyo, Naiara Aginako
Publicado en: Multimedia Tools and Applications, Edición Volume 83, 2023, ISSN 2213-7793
Editor: Springer
DOI: 10.1007/s11042-023-16664-4

Buscando datos de OpenAIRE...

Se ha producido un error en la búsqueda de datos de OpenAIRE

No hay resultados disponibles

Mi folleto 0 0