META-aivi uses artificial intelligence to accurately identify size variations of the pipes instantaneously. Using the fast counting feature, all the different parts are classified and counted within seconds.
SolVision’s superior recognition capabilities ensures that OCR of bicycles can be accurately carried out regardless of how the identification numbers look or light refraction levels.
There are many types of defects that may appear differently each time on the stamped parts, in particular oil or water stains, which are not easily detected.
The optimization dilemma: a large number of defects Hard drive metal bases are vulnerable to many defects during production, from damages to the metal surface to incorrect shape or size.
Small, spiral-surfaced metal parts can be inspected using SolVision’s Instance Segmentation tool to learn the different types of cut marks or collision faults from sample images, then building an AI model to recognize these subtle defects.
