[Video Available] Appearance Inspection AI 'Roxy AI' Major Version Up!

Added features like "Attention Map" that achieve semseg with very simple annotations! Accuracy and speed have further improved!

High-precision and high-speed appearance inspection AI 'Roxy AI' has undergone its first major version upgrade! With this addition of features, we are lowering 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 detecting defects is semantic segmentation (hereafter referred to as "semseg"). High-performance models like Yolo have been released and are adopted by many appearance inspection AI products, but the annotation process for semseg is very cumbersome, making it a bottleneck for implementation. When the boundary between normal and defective is ambiguous, it can be difficult to annotate correctly. With the newly added proprietary 'Attention Map' in Roxy AI V2, this issue is dramatically improved. There is no need to be aware of the boundaries between normal and defective; simply clicking on the defective area is sufficient. This achieves semseg in an overwhelmingly efficient manner. ■ Learning Environment - Significantly improved detection capability for small objects in measurement AI - Official support for RTX 50 series - Support for learning on CPU - Various other improvements ■ Runtime Environment - Compatible with Keyence's LJ-S8000 - Added a group of workers to flexibly control inspection results

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