Geodesic
Architecture of multi-agent neurocognitive system providing semantic representation of multimodal images in technology of machine vision
News of the Kabardin-Balkar scientific center of RAS, no. 1 (2019), pp. 16-22.

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This article represents a method for formalizing the semantics of natural language patterns based on the self-organization of multi-agent neurocognitive architectures. An architecture has been developed for creating conceptual agents that provide a semantic representation of images in a computer vision system. The algorithm of image recognition and natural language understanding using multimodal interface is demonstrated.
Keywords: multi-agent system, natural language interface, image recognition, formal semantics, natural language understanding, intelligence system, neurocognitive architecture. 
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I. A. Pshenokova; O. V. Nagoeva; Z. A. Sundukov; V. A. Denisenko. Architecture of multi-agent neurocognitive system providing semantic representation of multimodal images in technology of machine vision. News of the Kabardin-Balkar scientific center of RAS, no. 1 (2019), pp. 16-22. http://geodesic.mathdoc.fr/item/IZKAB_2019_1_a2/

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