Ciência da Computação - TCC - FCI Higienópolis

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    TCC
    Predição de comportamentos antissociais através de autômatos finitos determinísticos (AFD) com base na hierarquia de necessidades de Maslow
    Arbache, Fernando Bastos (2024-06-10)

    Faculdade de Computação e Informática (FCI)

    O objetivo deste projeto é sinalizar a propensão de um sujeito ao comportamento antissocial através da modelagem de um Autômato Finito Determinístico (AFD) a partir dos modelos comportamentais de A.Maslow e Winnicott. O Autômato foi adequado aos padrões comportamentais e materiais através da criação de uma ferramenta que assiste a listagem de suspeitos em investigações criminais. Evitou-se dar um valor generalizado à intensidade subjetiva destes padrões na psiquê do indivíduo.
  • Imagem de Miniatura
    TCC
    Reconhecimento de notas musicais por meio de redes neurais
    Quagliano, Giulia Barbieri (2024-12-08)

    Faculdade de Computação e Informática (FCI)

    Music notation is a system that has been developed to represent a piece of music graphically so that it can be used by an artist to perform in a similar way to the composer’s idea. Although the older systems of musical no tation were able to convey some degree of musical meaning, many did not have ways of indicating the duration of the notes. In addition, there are still many early documents that contain handwritten scores that have not been converted into a digital form. The goal of this project is to enable the recognition of musical notes using a convolutional neural network to recognize and categorize these images, which can be used to digitize handwritten scores to assist in learning music or in musical analysis and study. Different neural network architectures will be studied and analyzed, evaluating their accuracy for different images of musical notes.
  • Imagem de Miniatura
    TCC
    Reconhecimento de notas musicais por meio de redes neurais
    Quagliano, Giulia Barbieri (2024-12-09)

    Faculdade de Computação e Informática (FCI)

    Music notation is a system that has been developed to represent a piece of music graphically so that it can be used by an artist to perform in a similar way to the composer’s idea. Although the older systems of musical no tation were able to convey some degree of musical meaning, many did not have ways of indicating the duration of the notes. In addition, there are still many early documents that contain handwritten scores that have not been converted into a digital form. The goal of this project is to enable the recognition of musi cal notes using a convolutional neural network to recognize and categorize these images, which can be used to digitize handwritten scores to assist in learning music or in musical analysis and study. Different neural network architectures will be studied and analyzed, evaluating their accuracy for different images of musical notes.