Active Learning (AL)

This module provides a placeholder for AL systems i.e., AI systems that can consult an authority (e.g., a human) in the cases where they lack data/information to take proper decisions. DevelopersJSI Developed in ProjectDeveloped in STARSTAR TrendArtificial Intelligence TypesSoftwareMachine Learning Used in ProjectUsed in STAR

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Fatigue Monitoring System (FaMS)

FaMS uses artificial intelligence (AI) models relying on machine learning to estimate fatigue exertion level and mental stress of subjects based on static data (e.g., age, weight, etc.) as well as dynamic data (e.g., HR, EDA, skin temperature). DevelopersSUPSI AlgorithmMachine Learning Developed in ProjectDeveloped in STARSTAR TrendArtificial Intelligence TypesSoftwareSystem Used in ProjectUsed in STAR

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Natural Language Processing (NLP)

Natural Language Processing related components, proof of concepts and recommendations to facilitate the interaction between humans and machines and to get contextual information enabling efficient collaboration. TRL3 DevelopersR2M Developed in ProjectDeveloped in STARSTAR Technical Categories (JRC)CommunicationNatural language processing TrendArtificial Intelligence TypesSoftwareMachine LearningSoftwareConsultancy and Support

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PyTorch

PyTorch is an open source machine learning framework that accelerates the path from research prototyping to production deployment. DevelopersLINUX Programming LanguagePython TrendArtificial Intelligence TypesSoftwareFrameworkSoftwareMachine Learning Website: pytorch.org

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Workers Activity Recognition (WAR)

The Worker Activity Recognition (WAR) utilizes wearable sensors to collect worker’s activity data and uses a machine learning model that classifies worker’s activities in the manufacturing line. DevelopersDFKI Developed in ProjectDeveloped in STARSTAR PredictWorker Action PreventCollision TargetManufacturing Line TypesSoftwareMachine Learning Used in ProjectUsed in STAR

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