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Titlebook: Artificial Intelligence; 19th Russian Confere Sergei M. Kovalev,Sergei O. Kuznetsov,Aleksandr I. Conference proceedings 2021 Springer Natur

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期刊全称Artificial Intelligence
期刊简称19th Russian Confere
影响因子2023Sergei M. Kovalev,Sergei O. Kuznetsov,Aleksandr I.
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Artificial Intelligence; 19th Russian Confere Sergei M. Kovalev,Sergei O. Kuznetsov,Aleksandr I. Conference proceedings 2021 Springer Natur
影响因子.This book constitutes the proceedings of the 19th Russian Conference on Artificial Intelligence, RCAI 2021, held in Moscow, Russia, in October 2021...The 19 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 80 submissions. The conference deals with a wide range of topics, categorized into the following topical headings: cognitive research; data mining, machine learning, classification; knowledge engineering; multi-agent systems and robotics; natural language processing; fuzzy models and soft computer; intelligent systems; and tools for designing intelligent systems. .
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Artificial Intelligence978-3-030-86855-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Unternehmen als Institution und Organisationrithms in order to use them with vision-based simultaneous localization and mapping (vSLAM) methods. We evaluate developed approaches in photo-realistic simulator in two modes: with ground-truth depths and neural network reconstructed depth maps as vSLAM input. We evaluate standard metrics in order to estimate exploration coverage.
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978-3-030-86854-3Springer Nature Switzerland AG 2021
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Julia Reydirectly into the shared extracellular space (ECS). There are multiple experimental evidence that non-synaptic interactions play the important role in biological neural circuits. We propose a model of multitransmitter neural ensembles where each neuron is represented as a finite state machine. An al
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el, the previous classification value is refined by increasing the similarity parameter. This architecture was used to determine the network state in intrusion detection systems. The paper describes an algorithm for learning the proposed structure of the ART-2m network in parallel mode. A comparativ
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