[White Paper Release] We changed only the input with the same AI model. False alarms in visual inspection also exist outside the algorithm.
When there are many false alarms in AI visual inspection, the cause is not solely the algorithm. Our company has fixed the parameters of the AI anomaly detection engine "E3 ENGINE" and conducted verification by changing the input from regular camera images (LIVE) to 3D images using the 3D imaging technology "FORESIGHT STEREO," compiling the results into a white paper.
■ The same 128 samples (35 good products and 93 defective products), imaging device TR-100
■ The overlapping band of scores for good and defective products was reduced by 84%, from Δ0.37 to Δ0.06
■ The number of false alarms at the optimal threshold was halved from 12 to 6 (while missed detections increased from 0 to 4)
An example where two good products, indistinguishable by visual inspection, received scores that differed by three times due to differences in reflection illustrates "whether AI was seeing shape or appearance," supported by concrete data.

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