[Video Available] There is a reason for the high accuracy of 'Roxy AI'!

Roxy AI's proud defect detection AI can accurately detect even very small defects and has contributed to the automation of inspections for many customers. However, the defect detection AI struggles with detecting defects that require a wide view of the image and unknown defects, which may not meet your expectations. The newly added good product learning AI excels at determining defects that the defect detection AI struggles with. Since the good product learning AI only learns from good product data, it can be used in environments where defects do not occur. There are three AIs that support the defect detection AI, including the good product learning AI: - Good product learning AI: Detects a wide range of defects, unknown defects, and human errors - Image generation AI: Generates high-quality training data for the defect detection AI - Zero learning measurement AI: Achieves size measurement and count without learning By combining these, flexible and high-precision inspection automation can be realized. A one-month trial is also available. Please give it a try.

The AI used for visual inspection places the utmost importance on accuracy. Many visual inspection AI products aim to improve accuracy by adding data or repeatedly tuning parameters until accuracy increases. To achieve high precision under the condition of having a limited number of defective samples, Roxy AI emphasizes data organization. In this version upgrade, various features have been added to make it even more user-friendly and to achieve even higher accuracy. - Judging the quality of shooting conditions before AI learning: It is often discovered after trial and error that the reason for low AI accuracy was poor imaging conditions. Roxy AI detects adverse conditions that could negatively impact AI learning before the learning process begins, minimizing unnecessary trial and error and rework. - Automatic data organization: There is no need to manually check large amounts of data thoroughly. By automatically excluding data deemed inappropriate by the AI during training, the time and labor required for data organization are reduced. - Additionally, an integrated viewer that allows observation of data from various perspectives, among other features.