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CORDIS - Risultati della ricerca dell’UE
CORDIS

Explainable Trustworthy brain-like AI for Data Intensive Applications

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Impact realisation roadmap (si apre in una nuova finestra)

Document outlining the roadmap for impact

Mid-project revision of the Data Management Plan (si apre in una nuova finestra)

Mid-project update (revision) of the Data Management Plan.

Requirements, use-case scenarios, specification and architecture (si apre in una nuova finestra)

Report describing the collected requirements and specification for use cases

Project reference manual (quality, risks and contingency plans) (si apre in una nuova finestra)

Reference manual for the project created at its start

Collaboration, clustering and standardization activities - halfway report (si apre in una nuova finestra)

Document outlining collaborative and clustering efforts and standardization activities - halfway report.

Business and sustainability analysis and planning - halfway report (si apre in una nuova finestra)

Document reporting halfway analysis of business and sustainability

Virtual training framework and environment for brain-like AI models - stage I (si apre in una nuova finestra)

Report on the development and validation of the proposed virtual framework for training brain-like neural networks (AI models) - first stage

Ethics Advisor's report 1 (si apre in una nuova finestra)

First report prepared by the external independent Ethics Advisor

Design, training, validation and deployment of brain-like neural networks in flexible learning scenarios (si apre in una nuova finestra)

Report on the initial development of brain-like neural networks and their validation in various flexible learning scenarios.

Data processing pipeline for data optimisation, explainability and federated learning - stage I (si apre in una nuova finestra)

Report on data processing pipelines with emphasis on the data optimisation and visualisation/explainability (stage I)

Explainable, trustworthy, transparent and ethical brain-like AI methods - stage I (si apre in una nuova finestra)

Report on the development of techniques for incorporating the explainability, trustworthiness and transparency criteria for data and models - introductory stage (outline)

Use-case implementation planning and evaluations - first stage (si apre in una nuova finestra)

Report on implementation, execution and evaluation of use cases - first stage (focus on implementation and validation)

OEI - Requirement No. 1 (si apre in una nuova finestra)

Ethics Advisor_It is not fully clear how the participants of the co-design, co-creation and evaluation activities will be recruited.The actual extent of personal data collection and processing is also not sufficiently described, since it is planned to integrate SSH disciplines such religious viewpoints for understanding the application areas, phycological, legal, and sociological aspects considering intersectional factors (gender, ethnicity, age, socioeconomic status, disability) (DoA Part B, page 19), while it is also stated in the self-assessment that information regarding race, gender, religion or political orientation will never be requested. Thus, it should be explained how all of the data intended to be processed in the project is relevant and limited to the purposes of the research project (in accordance with the ‘data minimisation ‘principle).The AI to be developed/used in the project may lead to discrimination of people, potential bias, social or economic disadvantage especially in the AI for Digital Finance sector (DoA Part B, page 16) where solutions are provided despite the lack of adequate quantity of training datasets. Therefore, the ethics risks related to the development/deployment of the AI systems/techniques should be evaluated more thoroughly and mitigation plans for potential negative social impacts should be considered.An independent Ethics Advisor should be appointed with a mandate to oversee the project activities, in particular task T1.4 and provide relevant requirements with regards to participation of humans, personal data protection and AI. Reports prepared by the external independent Ethics Advisor must be submitted as deliverables in M12 and 24.The applicant is invited to send the CV of the suggested Ethics Advisor and discuss their appointment with the Project Officer as soon as possible after the start of the action. Guidance for Ethics Advisors/Boards can be found under the European Commission Funding and Tenders portal.

Pubblicazioni

Spiking representation learning for associative memories (si apre in una nuova finestra)

Autori: Naresh Ravichandran; Anders Lansner; Anders Lansner; Pawel Herman; Pawel Herman; Pawel Herman
Pubblicato in: Frontiers in Neuroscience, 2024, ISSN 1662-453X
Editore: Frontiers in Neuroscience
DOI: 10.48550/ARXIV.2406.03054

Perception sensor integration for improved environmental reconstruction in quadruped robotics (si apre in una nuova finestra)

Autori: Christyan Cruz Ulloa, Jaime Del Cerro, Antonio Barrientos
Pubblicato in: Jornadas de Automática, 2024, ISSN 3045-4093
Editore: Universidade da Coruna
DOI: 10.17979/JA-CEA.2024.45.10830

Scientific Reports (si apre in una nuova finestra)

Autori: N. Chrysanthidis; F. Fiebig; A. Lansner; P. Herman
Pubblicato in: Scientific Reports, 2025, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/S41598-025-12611-5

Unsupervised representation learning with Hebbian synaptic and structural plasticity in brain-like feedforward neural networks (si apre in una nuova finestra)

Autori: Naresh Ravichandran, Anders Lansner, Pawel Herman
Pubblicato in: Neurocomputing, Numero 626, 2025, ISSN 0925-2312
Editore: Elsevier BV
DOI: 10.1016/J.NEUCOM.2025.129440

A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks (si apre in una nuova finestra)

Autori: Muhammad Ihsan Al Hafiz, Naresh Ravichandran, Anders Lansner, Pawel Herman, Artur Podobas
Pubblicato in: Lecture Notes in Computer Science, Applied Reconfigurable Computing. Architectures, Tools, and Applications, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-87995-1_12

Efficient Navigation for Quadruped Robots in Post-Disaster Scenarios

Autori: Cruz, C., Guijarro Tolón, J., del Cerro, J., Barrientos, A.
Pubblicato in: 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
Editore: 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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