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[Development Case] Automation of Sanitary Ware Appearance Inspection

Automating inspection processes that tend to be personalized through visual checks with advanced technology! Introduction of development cases.

Image recognition technology using Deep Learning is expected to be applied in visual inspection in industries such as manufacturing due to its high detection performance and generalization capabilities. Our company has achieved results in defect detection using object detection with Deep Learning through a Proof of Concept (PoC) in an automation project for sanitary ware visual inspection with LIXIL. We are currently advancing towards trial operations for line implementation. Regarding this development initiative, we presented jointly with LIXIL at the Interactive Session of the 2020 Annual Conference of the Japanese Society for Artificial Intelligence. [Development Example] ■ OS: Windows 10 Pro ■ Development Period: 2018 onwards ■ Number of Developers: 1 for PoC / 2 for main development (planned) ■ Development Languages: C#, Python ■ Network Used: SSD512 (VGG16) *For more details, please refer to the PDF document or feel free to contact us.

• Company：コンピュータマインド 東京本社
• Price：Other

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