Principle and design of a dynamic neural network for efficient and accurate recognition of a time-varying object based on its static patterns and its dynamic pattern variations

Chialun John Hu

doi:10.1117/12.805483

10 February 2009 Principle and design of a dynamic neural network for efficient and accurate recognition of a time-varying object based on its static patterns and its dynamic pattern variations

Chialun John Hu

Author Affiliations +

Proceedings Volume 7245, Image Processing: Algorithms and Systems VII; 724518 (2009) https://doi.org/10.1117/12.805483
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

Based on our research in the last 17 years (with 68 papers published) on the subject of artificial neural network studied from the point of view of N-dimension geometry, a novel neural network system, the dynamic neural network, is proposed here for detecting an unknown moving (or time-varying) object such that the object will not only be detected by its static images, but also by the way it moves if this object follows a constant moving pattern. The system is designed to identify the unknown object by comparing a few time-separated snapshots of the object to a few standard moving objects learned or memorized in the system. The identification is determined by a user entered accuracy control. It could be very accurate, yet still be quite robust and quite fast in identification (e.g., identification in real-time) because of the simplicity of the algorithm. It is different from most other neural network systems because it employs the ND geometrical concept.

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Chialun John Hu "Principle and design of a dynamic neural network for efficient and accurate recognition of a time-varying object based on its static patterns and its dynamic pattern variations", Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 724518 (10 February 2009); https://doi.org/10.1117/12.805483

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