AI portfolio of reference implementations: Difference between revisions

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[[A.7: RL4MachineTuning]]
[[A.7: RL4MachineTuning]]


A.8: [[Time prediction for flexible manufacturing]]
[[A.8: Time prediction for flexible manufacturing]]


A.9: [[LioNets on Time Series]]
[[A.9: LioNets on Time Series]]


A.10: [[HIRIT]]
[[A.10: HIRIT]]


A.11: [[DFDD]]
[[A.11: DFDD]]


A12: [[McDefect Solutions]]
[[A12: McDefect Solutions]]




'''B) WEEE & Battery'''
'''B) WEEE & Battery'''


B.1: [[Isaac Sim]]
[[B.1: Isaac Sim]]


B.2: [[Dexnet]]
[[B.2: Dexnet]]


B.3: [[YOLO: image detection architectures]]
[[B.3: YOLO: image detection architectures]]


B.4: [[NVIDIA kaolin tools and resources]]
[[B.4: NVIDIA kaolin tools and resources]]


B.5: [[PointNet++]]
[[B.5: PointNet++]]


B.6: [[ROS Noetic]]
[[B.6: ROS Noetic]]


B.7: [[RoboGraph]]
[[B.7: RoboGraph]]


B.8: [[Jupyddl]]
[[B.8: Jupyddl]]




'''C) Research'''
'''C) Research'''


C.1: [[JGNN Graph Neural Networks on Native Java]]
[[C.1: JGNN Graph Neural Networks on Native Java]]
   
   
C.2: [[Decentralized-gnn]]
[[C.2: Decentralized-gnn]]


C.3: [[Locally Private Graph Neural Networks]]
[[C.3: Locally Private Graph Neural Networks]]


C.4: [[Hugging Face]]
[[C.4: Hugging Face]]


C.5: [[SHapley Additive exPlanation (SHAP)]]
[[C.5: SHapley Additive exPlanation (SHAP)]]


C.6: [[DeepLIFT]]
[[C.6: DeepLIFT]]


C.7: [[EthicalML]]
[[C.7: EthicalML]]




'''D) All/Smart industry'''
'''D) All/Smart industry'''


D.1: [[AutoML]]
[[D.1: AutoML]]


D.2: [[DIDA (Digital Industries Data Analytics)]]
[[D.2: DIDA (Digital Industries Data Analytics)]]


D.3: [[Auto-Weka]]
[[D.3: Auto-Weka]]


D.4: [[ML.NET]]
[[D.4: ML.NET]]

Revision as of 07:32, 26 April 2023

The CircularTwain AI portfolio of reference implementations, presents a non-exhausting list of 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 implantations refer top. Further information on their description, type, AI breadth, related technologuesmlicense 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.7: RL4MachineTuning

A.8: Time prediction for flexible manufacturing

A.9: LioNets on Time Series

A.10: HIRIT

A.11: DFDD

A12: McDefect Solutions


B) WEEE & Battery

B.1: Isaac Sim

B.2: Dexnet

B.3: YOLO: image detection architectures

B.4: NVIDIA kaolin tools and resources

B.5: PointNet++

B.6: ROS Noetic

B.7: RoboGraph

B.8: Jupyddl


C) Research

C.1: JGNN Graph Neural Networks on Native Java

C.2: Decentralized-gnn

C.3: Locally Private Graph Neural Networks

C.4: Hugging Face

C.5: SHapley Additive exPlanation (SHAP)

C.6: DeepLIFT

C.7: EthicalML


D) All/Smart industry

D.1: AutoML

D.2: DIDA (Digital Industries Data Analytics)

D.3: Auto-Weka

D.4: ML.NET