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Universidade Federal do Rio de Janeiro

A study on deep convolutional neural networks for computer vision applications

Abstract

dc:description.abstract

Presents an Artificial Cortex model for solving complex problems. In the framework of the cortex, highlighting the use of machine learning based on multiple artificial neural networks. The design of the model of the observation of the functioning of the brain as a set of functional areas that operate in the process of cognition and subsequently use the acquired knowledge in decision-making and execution of complex actions. To experiment, observe and analyze the efficiency of the Cortex is decided by the application in an Intelligent Tutor System based on Digital Games, considering the teaching-learning process a complex subject, subjective and requires dynamism in their implementation (range strategies for Make the process flexible and personalized). The proposed tools are delimited through exploratory research, generating knowledge for practical use in the solution of problems related to education, such as applied research. Finally, statistical resources are used in order to explain the reality of the phenomenon, pointing out significant results (significance of 5%) in the improvement of learning, comparing teaching techniques.

Degree

thesis:*
Grantor dc:publisher
Universidade Federal do Rio de Janeiro
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Estevão Filho, Roberto de Moura
Advisor dc:contributor.advisor
  • Gomes, José Gabriel Rodríguez Carneiro

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • Acesso Aberto
Language dc:language
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11422/6098
OAI identifier oai:identifier
oai:pantheon.ufrj.br:11422/6098

Chain of custody

source
Harvested from
Brazil UERJ
Base URL
pantheon.ufrj.br/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Estevão Filho, Roberto de Moura. A study on deep convolutional neural networks for computer vision applications. Universidade Federal do Rio de Janeiro, 2017. http://hdl.handle.net/11422/6098