Objective
Real-time classification of visible defects on flat and moving materials is a critical issue in quality control and management in many process-oriented industries.
ONNI-ADC aims to develop an advanced defect classification system prototype which will be based on a neural network system approach and OMI technologies.
The prototype will be tested in a real user manufacturing plant to validate the system performances and the results for the targeted markets.
The ONNI-ADC development process will consist of the identification of the needs and the requirements of potential users in Europe in sectors such as steel, aluminium and paper; the development of OMI neural network supercells; and the prototyping and testing of the final OMI-based defect classification system in a steel-making plant.
Fields of science
Topic(s)
Data not availableCall for proposal
Data not availableFunding Scheme
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92126 Montrouge
France