Hardware Neural Network for a Visual Inspection System
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概要
- 論文の詳細を見る
The visual inspection of defects in products is heavily dependent on human experience and instinct. In this situation, it is difficult to reduce the production costs and to shorten the inspection time and hence the total process time. Consequently people involved in this area desire an automatic inspection system. In this paper, we propose a hardware neural network, which is expected to provide high-speed operation for automatic inspection of products. Since neural networks can learn, this is a suitable method for self-adjustment of criteria for classification. To achieve high-speed operation, we use parallel and pipelining techniques. Furthermore, we use a piecewise linear function instead of a conventional activation function in order to save hardware resources. Consequently, our proposed hardware neural network achieved 6GCPS and 2GCUPS, which in our test sample proved to be sufficiently fast.
- （社）電子情報通信学会の論文
- 2008-04-01
著者
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Hayakawa Yoshihiro
Laboratory For Brainware/laboratory For Nanoelectronics And Spintronics Research Institute Of Electr
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Hayakawa Yoshihiro
Laboratory For Brainware Reseach Institute Of Electrical Comunication Tohoku University:laboratory F
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Nakajima Koji
Laboratory For Brainware/laboratory For Nanoelectronics And Spintronics Research Institute Of Electr
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Nakajima Koji
Laboratory For Brainware Reseach Institute Of Electrical Comunication Tohoku University:laboratory F
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CHUN Seungwoo
Laboratory for Brainware/Laboratory for Nanoelectronics and Spintronics Research Institute of Electr
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Chun Seungwoo
Laboratory For Brainware/laboratory For Nanoelectronics And Spintronics Research Institute Of Electr
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