The MUHAI project created educational materials, especially video tutorials and webinars on aspects of AI covered by the project. read more of MUHAI #trAIning

Educational kits for civil society, industry and policy. Easy-to-understand resources explaining AI bias and fairness. Designed for anyone—no technical background required. Practical case studies showing real-world examples. read more of DIVERSIFAIR toolkits on Intersectional Fairness in AI

Compliance with safety standards is essential in safety-critical domains like automotive, rail and space. While traditional approaches to functional safety are well-established, the introduction of AI into safety-critical systems presents new complexities... read more of Explainable AI for Systems with Functional Safety Requirements

Good practice usage guides about the baseline technology of the iMagine AI platform read more of Best practices and Guidelines for Developers and providers of AI-based Image Analytic Services

Good practice usage guides about the baseline technology of the iMagine AI platform read more of Best practices and Guidelines for Developers and providers of AI-based Image Analytic Services

Best practice document on image analysis with AI, with a specific focus on aquatic sciences but applicable to any research field read more of Best practices for producers and providers of image sets and image analysis applications in aquatic sciences

Best practice document on image analysis with AI, with a specific focus on aquatic sciences but applicable to any research field read more of Best practices for producers and providers of image sets and image analysis applications in aquatic sciences

The application of automated inspection for industrial pipe damage detection is attracting substantial research and development interest. Damage to pipes not only hinders the optimal functioning of factories but also presents a risk of industrial disaster... read more of Advancing Industrial inspection: A Dataset for Automated Damage Detection in Insulated Pipes

As Deep Neural Network (DNN)-based algorithms are improving, pivotal changes are happening towards efficient and effective automation in the field of industrial inspection. In the scope of our project, we analyze X-ray images of steel pipelines to detect ... read more of X-ray Anomaly Detection in Industrial Pipelines

Damage detection remains a critical challenge, especially within the industrial automation sector, necessitating the development of advanced inspection technologies and their potential applications. Conventional industrial inspection methods are hindered ... read more of Foreground-Aware Knowledge Distillation for Enhanced Damage Detection