XMANAI Hybrid model
EU-funded XMANAI project deals with bringing explainable AI to the Industry, and this asset is an example of the models developed during the project.
AI in Manufacturing is a topic of growing importance in many area such as smart manufacturing and Industry 4.0. This section presents references on on-going projects, pilot experiments in the field and initial results in that area.
EU-funded XMANAI project deals with bringing explainable AI to the Industry, and this asset is an example of the models developed during the project.
Nine YouTube video lectures from winter school organized within DIH4AI project by DIH-CIIRC and coorganized by Munich and Saxony-Anhalt DIHs
The presented service offers a new annotation tool, developed to facilitate image annotation needs in the RECLAIM project.
A workflow for the specific case of process monitoring data which contains cycles repeating over a long time is presented. The method relies on predefined features ideally used as health-indicators which are aggregated over the cycles. Anomaly detection, ...
Atcrecognize extracts text from images that contain label tags. Using its underlying deep learning technology, atcrecognize enhances the image, removes the unnecessary parts of the image, and feeds into the ocr model that extracts the text with more preci...
Apache StreamPipes is a self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams. The Apache StreamPipes Python Client is a new library targeted at data scientists, which helps to easily interact...
This dataset contains hyperspectral images of denim fabric over 224 reflectance bands. It was used to test automated composition analysis in the DIH4AI Open Call 2 FABCOD project (Fabric Composition Detector).
Modern manufacturing environments strive to support a great variety of products, driven by the large customization demand, while at the same time maintain low cost and fast response to the market. To cope with the challenging manufacturing requirements, o...
Discover one of the breakthrough achievements of the ESFA project, a pioneer project in the field of Artificial Intelligence applied to Climate Prediction. Leveraging Geoskop’s revolutionary AI algorithms, housed in a Docker image, we provide unprecedente...
The AI4CNC experiment is designed to develop a Federated Learning System Platform for CNC machines to estimate tool wear through AI models and secure data sharing. The main objective is to use data from TEKNOPAR's CNC machines and sensors to estimate tool...
Demonstrations of using the COALA assistant in the white goods use case with Augmented Manufacturing Analytics function.
A flexible and extensible synthetic data generation engine based on mainstream statistics distributions and on timeseries generative AI techniques.