(Please insert an screenshot of the Tool)
Type of tool: Web application
Required skills:
- Elementary User: No programming
- Advanced User: Python, Basic Deep Learning (PyTorch)
Short description of the tool:
- Detailed description: Data Extractor/MatrixDataExtractor_UserGuide.pdf
Disclaimer:
Matrix Data Extractor tool is funded by the Interreg North-West Europe program (Interreg NWE), project Di-Plast - Digital Circular Economy for the Plastics Industry (NWE729, https://www.nweurope.eu/projects/project-search/di-plast-digital-circular-economy-for-the-plastics-industry/ ). Any support to provide table detection model will not be provided unfortunately. The accuracy of table detection model depends on various factors such as volume, variety of annotated datasets, hyperparameters of model. You can do your experiment to get better accuracy of your table detection model.
How to use/download/access it:
e.g. Get the GitHub https://github.com/cslab-hub/MatrixDataExtractor, copy
the code into your computer and start using
_Use case/problem:
Selecting material (recyclate) for specific product requirements
Description of the problem the tools solves:
[General] + [Tool-specific]
Contact person of the tool: A
Related tools:
- Analyse and Visualize your process data with data analytics -> Data Analytics
- Get guidance to set up a working data infrastucture -> Data Infrastructure Wiki
- Find the right sensor to survey your process -> Sensor Tool
- Improve internal information and material flow -> VSM
- Match material requirements with material properties -> Matrix