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Abstract

Disclosed is an AI-based product surface inspecting apparatus. The AI-based apparatus includes: a sensor unit photographing a product to generate image data and measures a color, a saturation, a brightness, a transparency, and/or a reflectance of the product; a detection unit detecting a defect on the product by inputting the image data to a convolutional neural network (CNN) trained to detect a defect on a product surface; and a preprocessor converting the image data based the color, the saturation, the brightness, the transparency, and/or the reflectance of the product to input the converted data to the detection unit. The number of convolution layers of the convolutional neural network is determined based on a defect detection difficulty determined according to at least one of the color, the saturation, the brightness, the transparency, and the reflectance of the product and a defect type.

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First Claim