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. 
@article{IZKAB_2019_1_a2,
     author = {I. A. Pshenokova and O. V. Nagoeva and Z. A. Sundukov and V. A. Denisenko},
     title = {Architecture of multi-agent neurocognitive system providing semantic representation of multimodal images in technology of machine vision},
     journal = {News of the Kabardin-Balkar scientific center of RAS},
     pages = {16--22},
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     number = {1},
     year = {2019},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/IZKAB_2019_1_a2/}
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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/