B.12: Object Detection and Classification for PC Components: Difference between revisions
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• '''Asset Type''': Executable | • '''Asset Type''': Executable | ||
• '''AI Breadth''': | • '''AI Breadth''': ML | ||
• '''Learning Ability''': | • '''Learning Ability''': Neural Networks | ||
• '''Related technologies''': | • '''Related technologies''': N.A | ||
• '''Applicable Research Area''': | • '''Applicable Research Area''': Collaborative AI | ||
• '''Applicable Technical Category''': | • '''Applicable Technical Category''': Computer Vision | ||
• '''License Information | • '''License Information''': Copyright | ||
• '''Related to circularity and sustainability''': Yes | • '''Related to circularity and sustainability''': Yes | ||
Latest revision as of 09:48, 28 April 2025
• Short Description: Advanced Object Detection and Classification Module: Incorporates pretrained neural network models for precise object detection and classification, embedded within the process Digital Twin, utilizing NOVAAS technology for optimal performance. The system integrates the YOLO v5 model for advanced object detection and classification within the Digital Twin software, using NOVASS technology. It employs industry standards, protocols, and APIs for seamless execution and interoperability, offering precise object recognition and improved decision-making across sectors.
• Reference, URL: https://www.uninova.pt/
• Applicable Business Category: Manufacturing
• Application in relevant Projects/Initiatives: Yes, Circular TwAIn
• Asset Type: Executable
• AI Breadth: ML
• Learning Ability: Neural Networks
• Related technologies: N.A
• Applicable Research Area: Collaborative AI
• Applicable Technical Category: Computer Vision
• License Information: Copyright
• Related to circularity and sustainability: Yes
• Audience:
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