Achieving high precision with data-centric approach! Appearance inspection AI 'Roxy AI'

High-precision, high-speed appearance inspection AI 'Roxy AI' has undergone its first major version upgrade! With this addition of features, we have lowered the barriers to implementing AI inspections more than ever before, achieving stabilization of inspection process quality and cost reduction. ■ Attention Map A representative method for defect detection is semantic segmentation (hereafter referred to as semseg). High-performance models such as Yolo have been released, and many appearance inspection AI products have adopted them; however, the annotation for semseg is very cumbersome, which has become a bottleneck for implementation. When the boundary between normal and defective is ambiguous, it is even difficult to annotate correctly. With the newly added unique 'Attention Map' in Roxy AI V2, this problem is dramatically improved. There is no need to be conscious of the boundaries between normal and defective; simply clicking on the defective area is sufficient. This achieves semantic segmentation in an overwhelmingly efficient manner. ■ Learning Environment - Significantly improved detection capability of small objects in measurement AI - Official support for RTX 50 series - Support for learning on CPU - Other numerous improvements ■ Runtime Environment - Compatible with KEYENCE's LJ-S8000 - Added a group of workers to flexibly control inspection results