Technical Support: Spectral Lighting and General Lighting
Learn from images of spectral lighting and general lighting to detect anomalies!
The manufacturer we consulted this time is a company that has been inquiring with us for some time. They sent us sample images. Our company also conducts usage explanations and demonstrations via web conference. First, it would be smoother to enter the verification process after asking about the client's issues and operational status during the web conference. ■ Inspection Settings and Results We conducted learning and processing on the two types of images provided, one with spectral lighting and the other with general lighting. For both images, we specified abnormal areas and trained the system to identify them. In the spectral lighting image, we were able to detect some potentially defective areas, and I feel there is a possibility to improve detection accuracy by increasing the training data. In the general lighting image, it honestly seems difficult to make judgments. It appears challenging to detect anything other than large, grainy defects like those in the image on the right. The left image shows the detection of defects in the spectral lighting image. The numbers in the detection image represent the AI's confidence level in percentage, which we refer to as the number of recognition points.
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