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No crystal ball needed – The future of AI and visual inspection is here
Hello from the B.E. Exchange team.
Visual inspection is a proven test method that detects cosmetic and particulate defects in the packaging and contents of pharmaceutical products using a system of high-resolution cameras.
This method, however, is considered a probabilistic and non-deterministic test due to the following factors effecting the ability to detect a specific defect:
- The color and opalescence of the product and the container
- The position of the product at the time images are captured
- The presence of shadows which may create ambiguous images
Neural networks offer significant assistance in overcoming these problems, increasing the precision of the visual inspection tests, and reducing the influence of external variables. An automation system using the capabilities of Artificial Intelligence (AI) does not use algorithms based on rigid parameters, but analyzes the images in a flexible manner, using a large set of data that it examines in sequence.
Read the numerous advantages to applying neural networks to visual inspection on our latest article: The future of Visual Inspection for quality testing in pharmaceuticals.
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