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.
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.
SolVision elevates quality control in electronics with AI capable of defect detection and classification of metal casings that have reflective surfaces.