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[Development Case] Development of Food Foreign Matter Inspection Equipment

Improving the performance and cutting costs of existing systems! Introducing a case study on the development of food foreign matter inspection equipment.

Our company has successfully detected a large number of foreign objects that were previously missed by applying Deep Learning object detection technology to images captured by inspection equipment. In image processing, it is common to handle complex processing steps sequentially, which can lead to longer processing times per inspection, ultimately affecting overall production efficiency. With this technology, we have achieved high-speed inspections of approximately 100ms or less per inspection (per image), allowing us to improve inspection accuracy without compromising production efficiency. [Development Example] - OS: Windows 10 Pro - Development Period: 6 months - Number of Developers: 2 - Programming Languages: C#, C++, Python - Networks Used: SSD, Yolov3 *For more details, please refer to the PDF document or feel free to contact us.