【摘 要】
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The cellular neural/nonlinear network(CNN)is a powerful tool for image and video signal processing,robotic and biological visions.This paper introduces a kind
【出 处】
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Communications in Theoretical Physics
论文部分内容阅读
The cellular neural/nonlinear network(CNN)is a powerful tool for image and video signal processing,robotic and biological visions.This paper introduces a kind of CNNs with performance of extracting closed domainsin binary images,and gives a general method for designing templates of such a kind of CNNs.One theorem providesparameter inequalities for determining parameter intervals for implementing prescribed image processing functions,respectively.Examples for extracting closed domains in binary scale images are given.
The cellular neural / nonlinear network (CNN) is a powerful tool for image and video signal processing, robotic and biological visions. This paper introduces a kind of CNNs with performance of extracting closed domains in binary images, and gives a general method for designing templates of such a kind of CNNs OneOne theorem providesparameter inequalities for determining parameter intervalsAnnouncement of prescribed image processing functions, respectively. Samples for extracting closed domains in binary scale images are given.
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