Umbo Cv Inc.

Memorence Ai Co., Ltd.

Pai-Heng Hsiao

Ping-Lin Chang

System and method for intelligently monitoring the production line that can monitor an inspected object image captured by an image capturing device, thereby allowing an operating station host to provide a labeling module to reinspect a classification decision of a classifier subsystem, to achieve the purpose of verifying the classification decision or checking whether there are missed inspections. In addition, the classifier subsystem can automatically filter out classification decisions with lower reliability to effectively reduce the number of reinspection. Moreover, a group of inspected object images can be analyzed first to obtain image difference features through comparison, which is suitable for insufficient training samples. Furthermore, the labeling module can simultaneously reinspect highly relevant historical classification decisions. Meanwhile, a second image capturing device is provided, so that the system can automatically label defect positions based on the inspected object image before and after repair, thereby learning to judge whether defects occur.

System and method for intelligently monitoring a production line

A system and method for providing high resolution image through super-resolution reconstruction. The system comprises a frame buffer, a convolutional neural network module, an image processing module, and a bi-directional prediction module. After the frame buffer has received high-resolution image with low frames per second and low-resolution image with high frames per second, both are captured by an image capturing module, image processing with super-resolution reconstruction can be performed through the cooperation of the convolutional neural network module, the image processing module and the bi-directional prediction module. In other words, a frame with super-resolution can be calculated through a well-trained convolutional neural network.

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Taipei, Taiwan

Pai-Heng Hsiao