Abstract: An automatic target image acquisition and calibration system for application in a defect inspection system is disclosed. During the defect inspection system working normally, the automatic target image acquisition and calibration system is configured to find a recognition structure from an article under inspection, and then determines a relative position and a relative 3D coordinate if the article. Therefore, a robotic arm is controlled to carry a camera to precisely face each of a plurality of inspected surfaces of the article, such that a plurality of article images are acquired by the camera. It is worth explaining that, during the defect inspection of the article, there is no need to modulate an image acquiring height and an image acquiring angle of the camera and an illumination of a light source.

Abstract: A surface inspection system for foil article is disclosed. The surface inspection system comprises a box having a top long narrow opening and a bottom long narrow opening, a bridge interface, a first light source, a second light source, a first modular camera device having a first camera, and a second modular camera device having a second camera. In which, the first light source, the second light source, the first modular camera device, and the second modular camera device all accommodated in the box, and are coupled to a control box through the bridge interface. Particularly, this surface inspection system is allowed to be integrated in an automatic production line of a foil article like electro-forming aluminum foil (also called electronic aluminum foil), so as to achieve an in-line inspection of the surface morphology of the electro-forming aluminum foil.

Abstract: A defect inspection system is disclosed, and comprises a linear light source, N number of cameras, a display device, a tag reader, and a modular electronic device, in which the linear light source, the cameras and the modular electronic device are used for conducting a defect inspection of an article. On the other hand, the display device, the tag reader and the modular electronic device are adopted for conducting in production of at least one labeled example. Therefore, the modular electronic device is allowed to apply a machine learning process to an image classifier under using a training dataset containing the labeled examples, thereby producing at least one new defect recognition model or updating the existing defect recognition model.

Abstract: A motor controlling system is disclosed. The motor controlling system is integrated in an apparatus having roll-to-roll mechanism, and comprises a linear light source, N number of cameras and a modular electronic device. When a roll of continuous web material is discharged by an unwinding unit of the roll-to-roll mechanism so as to be further transferred to an inspection unit, the cameras are controlled by the modular electronic device to capture a plurality of time-consecutive material image frames. Subsequently, the modular electronic device conducts a defection inspection for a segment of the continuous web material by applying an image process to the material image frames. As a result, in case of there being at least one defect found, the modular electronic device stops a plurality of motors of the apparatus from running, thereby making the segment of the continuous web material be positioned on an inspection platform.

Abstract: A decision factors analyzing device and a decision factors analyzing device for analyzing a plurality of decision factors which cause a product of a product type to be purchased are provided. The method includes identifying a plurality of product sequences corresponding to the product type from a plurality of browse history data and a plurality of purchase history data corresponding to a plurality of consumers of a consumer database, wherein each of the product sequences includes a unpurchased product and a purchased product; obtaining a feature sequence according to the produce sequences and a plurality of product information; training a regression model corresponding to the product type according to K decision factors of the feature sequence to obtain an optimized regression model, and obtaining K decision values respectively corresponding to the K decision factors according to the optimized regression model to generate a decision factor sequence corresponding to the product type.

Abstract: A decision factors analyzing device and a decision factors analyzing device for analyzing a plurality of decision factors which cause a product of a product type to be purchased are provided. The method includes identifying a plurality of product sequences corresponding to the product type from a plurality of browse history data and a plurality of purchase history data corresponding to a plurality of consumers of a consumer database, wherein each of the product sequences includes a unpurchased product and a purchased product; obtaining a feature sequence according to the produce sequences and a plurality of product information; training a regression model corresponding to the product type according to K decision factors of the feature sequence to obtain an optimized regression model, and obtaining K decision values respectively corresponding to the K decision factors according to the optimized regression model to generate a decision factor sequence corresponding to the product type.