Description

The three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems, BRACIS 2023, which took place in Belo Horizonte, Brazil, in September 2023.

The 90 full papers included in the proceedings were carefully reviewed and selected from 242 submissions. They have been organized in topical sections as follows:

Part I: Best papers; resource allocation and planning; rules and feature extraction; AI and education; agent systems; explainability; AI models;

Part II: Transformer applications; convolutional neural networks; deep learning applications; reinforcement learning and GAN; classification; machine learning analysis;

Part III: Evolutionary algorithms; optimization strategies; computer vision; language and models; graph neural networks; pattern recognition; AI applications.

Intelligent Systems: 12th Brazilian Conference, BRACIS 2023, Belo Horizonte, Brazil, September 25–29, 2023, Proceedings, Part I

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Paperback / softback by Murilo C. Naldi , Reinaldo A. C. Bianchi

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Short Description:

The three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems,... Read more

    Publisher: Springer International Publishing AG
    Publication Date: 13/10/2023
    ISBN13: 9783031453670, 978-3031453670
    ISBN10: 3031453670

    Number of Pages: 483

    Non Fiction , Computing

    Description

    The three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems, BRACIS 2023, which took place in Belo Horizonte, Brazil, in September 2023.

    The 90 full papers included in the proceedings were carefully reviewed and selected from 242 submissions. They have been organized in topical sections as follows:

    Part I: Best papers; resource allocation and planning; rules and feature extraction; AI and education; agent systems; explainability; AI models;

    Part II: Transformer applications; convolutional neural networks; deep learning applications; reinforcement learning and GAN; classification; machine learning analysis;

    Part III: Evolutionary algorithms; optimization strategies; computer vision; language and models; graph neural networks; pattern recognition; AI applications.

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