Talking about Automotive Functional Safety at Automotive SPIN Italia
Safexplain project partner EXIDA-dev presented at the 21st Workshop on Automotive Software and Systems hosted by Automotive SPIN Italia
Integrating Explainable AI techniques into Machine Learning Life Cycles
Written by Robert Lowe & Thanh Bui, Humanized Autonomy Unit, RISE, Sweden. Machine Learning life cycles for data science projects that deal with safety critical outcomes require assurances of expected outputs at each stage of the life cycle for them to be...
SAFEXPLAIN to present in COMPSAC Autonomous Systems Symposium
The paper “Efficient Diverse Redundant DNNs for Autonomous Driving”, coauthored by BSC authors Martí Caro, Jordi Fornt and Jaume Abella, has been accepted for publication in the 47th IEEE International Conference on Computers, Software & Applications...
SAFEXPLAIN Presentation on Safe and Explainable Critical Embedded Systems Based on AI at DATE Conference in Antwerp
SAFEXPLAIN presented its latest research on Safe and Explainable Critical Embedded Systems Based on AI at the Design, Automation and Test in Europe Conference (DATE) in Antwerp, Belgium. The DATE conference is a leading event for electronic system design and test,...
Status at month 6: The SAFEXPLAIN consortium meets at IKERLAN
Figure 1: Members of the SAFEXPLAIN consortium meet at IKERLAN’s headquarters SAFEXPLAIN partners spent two days in IKERLAN presenting the work carried out in the first six months of the project. Although project partners have been meeting frequently online to...
Towards the Safety of Critical Embedded Systems Based on Artificial Intelligence: the Standardization Landscape
AI safety means ensuring that the operation of an AI system does not contain any unacceptable risks . It is essential to ensure that the AI system operates reliably, that unintended behavior is mitigated and that it is possible to explain how the AI system arrived at a particular decision
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