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Neocognitron with improved bend-extractors: Recognition of handwritten digits in the real world

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Abstract

We have reported previously that the performance of a neocognitron can be improved by a built-in bend-extracting layer. The conventional bend-extracting layer can detect bend points and end points of lines correctly, but not always crossing points of lines. This paper shows that an introduction of a mechanism of disinhibition can make the bend-extracting layer detect not only bend points and end points, but also crossing points of lines correctly. This paper also demonstrates that a neocognitron with this improved bend-extracting layer can recognise handwritten digits in the real world with a recognition rate of about 98%. We use the technique of dual thresholds for feature-extracting S-cells, and higher threshold values are used in the learning than in the recognition phase. We discuss how the threshold values affect the recognition rate.

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Fukushima, K., Kimura, E. & Shouno, H. Neocognitron with improved bend-extractors: Recognition of handwritten digits in the real world. Neural Comput & Applic 7, 260–272 (1998). https://doi.org/10.1007/BF01414887

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