Detection and Recognition of Visual Geons Based on SpecificObject of Interest Imaging Technology

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Abstract
In various fields including visual processing, computer graphics, neuroscience, and biological sciences, geons are widely recognized as fundamental units of complex shapes. Their importance has been broadly acknowledged. However, accurately identifying and extracting these geons remains a challenge.This study integrates theories from signal processing, computer graphics, neuroscience, and biological sciences, utilizing "object imaging" and neural networks to describe mathematical operators, in order to reveal the essence of visual geons. Experiments validate the core hypothesis of geon theory, namely that geons are foundational components for the visual system to recognize complex objects. Through training, neural networks are capable of identifying distinct basic geons and, based on this foundation, performing target recognition in more complex scenarios. This effectively confirms the existence of geons and their critical role in visual recognition, providing new tools and theoretical foundations for related research fields.
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