AI portfolio of reference implementations: Difference between revisions
No edit summary |
No edit summary |
||
| (4 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
The '''CircularTwain | The '''CircularTwain portfolio of AI reference implementations''', presents a non-exhausting list of reference AI implementations, as identified from the project’s partners and which have found to be relevant to the project's scope and activities. | ||
This portfolio is anticipated to be improved and evolve continuously throughout the CircularTwain project’s implementation, in order to record and describe further new AI implementations. | This portfolio is anticipated to be improved and evolve continuously throughout the CircularTwain project’s implementation, in order to record and describe further new AI implementations. | ||
An initial categorisation has been made based on the applicable domain/industry, these | An initial categorisation has been made based on the applicable domain/industry, these implementations refer to. Further information on their description, type, AI breadth, related technologies, license information, etc.are provided in each implementation's dedicated page. | ||
'''A) Manufacturing''' | '''A) Manufacturing''' | ||
| Line 30: | Line 30: | ||
[[A12: McDefect Solutions]] | [[A12: McDefect Solutions]] | ||
[[A13: AI Aided Disassembly Planner]] | |||
[[A14: Anomaly Detection Module for PETRO Industry]] | |||
[[A15: AI Aided Disassembly Planner]] | |||
[[A16: Best Practices (IT Equipment Recovery)]] | |||
[[A17: FA³ST AAS for Circular Economy]] | |||
| Line 49: | Line 59: | ||
[[B.8: Jupyddl]] | [[B.8: Jupyddl]] | ||
[[B.9: Decision Support System]] | |||
[[B.10: Disassembly Digital Twin]] | |||
[[B.11: LIB Cells Health State Digital Twin]] | |||
[[B.12: Object Detection and Classification for PC Components]] | |||
[[B.13: Waste Management Best Practices]] | |||
| Line 77: | Line 98: | ||
[[D.4: ML.NET]] | [[D.4: ML.NET]] | ||
[[D.5: AI Application Toolkit]] | |||
[[D.6: AutoML Tool]] | |||
[[D.7: Behaviour Tree Editor]] | |||
[[D.8: Circular TwAIn Ontology Library]] | |||
[[D.9: Collaborative Environment for AI Developments]] | |||
[[D.10: Human Digital Twin]] | |||
[[D.11: Hybrid Digital Twin]] | |||
[[D.12: Mechanical Recycling Digital Twin]] | |||
[[D.13: NOVAAS]] | |||
[[D.14: Process Digital Twin]] | |||
[[D.15: Product Digital Twin]] | |||
[[D.16: XAI for Unstructured Data]] | |||
Latest revision as of 08:01, 11 March 2025
The CircularTwain portfolio of AI reference implementations, presents a non-exhausting list of reference AI implementations, as identified from the project’s partners and which have found to be relevant to the project's scope and activities.
This portfolio is anticipated to be improved and evolve continuously throughout the CircularTwain project’s implementation, in order to record and describe further new AI implementations. An initial categorisation has been made based on the applicable domain/industry, these implementations refer to. Further information on their description, type, AI breadth, related technologies, license information, etc.are provided in each implementation's dedicated page.
A) Manufacturing
A.1: AI REGIO Supervised Learning for Multivariant Time Series Forecasting
A.2: AI REGIO-S5 Enterprise Big Data Analytics Suite: Manufacturing
A.3: AI REGIO Intelligent Computer Vision for Digital Twin
A.4: AI REGIO Reinforcement Learning for Assembly Line Balancing Enhancement
A.5: AI REGIO - Supervised real-time 2D-based Object Detection System
A.6: AI REGIO Industrial Faults Predictive Maintenance (IFPM)
A.8: Time prediction for flexible manufacturing
A13: AI Aided Disassembly Planner
A14: Anomaly Detection Module for PETRO Industry
A15: AI Aided Disassembly Planner
A16: Best Practices (IT Equipment Recovery)
A17: FA³ST AAS for Circular Economy
B) WEEE & Battery
B.3: YOLO: image detection architectures
B.4: NVIDIA kaolin tools and resources
B.10: Disassembly Digital Twin
B.11: LIB Cells Health State Digital Twin
B.12: Object Detection and Classification for PC Components
B.13: Waste Management Best Practices
C) Research
C.1: JGNN Graph Neural Networks on Native Java
C.3: Locally Private Graph Neural Networks
C.5: SHapley Additive exPlanation (SHAP)
D) All/Smart industry
D.2: DIDA (Digital Industries Data Analytics)
D.8: Circular TwAIn Ontology Library
D.9: Collaborative Environment for AI Developments
