{"id":28547,"date":"2023-09-27T11:07:53","date_gmt":"2023-09-27T09:07:53","guid":{"rendered":"https:\/\/bi-rex.it\/portfolio-items\/machine-learning-per-visual-inspection-e-controllo-qualita-ml4vi\/"},"modified":"2023-10-11T11:32:49","modified_gmt":"2023-10-11T09:32:49","slug":"machine-learning-for-visual-inspection-and-quality-control-ml4vi","status":"publish","type":"avada_portfolio","link":"https:\/\/bi-rex.it\/en\/portfolio-items\/machine-learning-for-visual-inspection-and-quality-control-ml4vi\/","title":{"rendered":"Machine learning For visual inspection and quality control \u2013 ML4VI"},"content":{"rendered":"

ML4VI<\/h1><\/div>

For visual inspection and quality control<\/h2>\n<\/div>

<\/i><\/i><\/span>Nature of the project and Objectives<\/span><\/a><\/h3><\/div>
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The overall objective of the ML4VI project is the identification, testing and tuning of an innovative approach, which bases the development of product quality control and visual inspection systems on the use of Artificial Intelligence and automatic training techniques<\/strong> (Machine Learning and Deep Learning), starting from acquired images and measurements of some physical characteristics of products, thus arriving at the realization of a suite of deep network architectures that can be easily re-trained and re-applied as the product type changes. The scope of ML4VI is therefore aimed at increasing the competitiveness of enterprises, particularly by improving their product quality control phase, and innovating their production processes. Testing and validation of the approach will take place by addressing Use Cases brought by partner companies, and validation of the results will be implemented with demonstration of a prototype system in an operational environment.<\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>Role played by BI-REX<\/span><\/a><\/h3><\/div>
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