dc.contributor | Peixoto, Helton Maia | |
dc.contributor | http://lattes.cnpq.br/6008562495410718 | |
dc.contributor | http://lattes.cnpq.br/8709900833456787 | |
dc.contributor | Magalhães, Rafael Marrocos | |
dc.contributor | Silva, Bruno Marques Ferreira da | |
dc.contributor | Vidal, Francisco José Targino | |
dc.creator | Menezes, Richardson Santiago Teles de | |
dc.date.accessioned | 2022-08-23T12:14:42Z | |
dc.date.accessioned | 2022-10-06T13:10:15Z | |
dc.date.available | 2022-08-23T12:14:42Z | |
dc.date.available | 2022-10-06T13:10:15Z | |
dc.date.created | 2022-08-23T12:14:42Z | |
dc.date.issued | 2022-07-22 | |
dc.identifier | MENEZES, Richardson Santiago Teles de. ChessPy: ferramenta para detecção inteligente de peças de xadrez. 2009. 54f. Trabalho de Conclusão de Curso (Graduação em Engenharia de Computação), Departamento de Engenharia de Computação e Automação, Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2022. | |
dc.identifier | https://repositorio.ufrn.br/handle/123456789/49204 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3964876 | |
dc.description.abstract | Chess is one of the most researched domains in artificial intelligence history. The most powerful programs are based on sophisticated research techniques, domain-specific adaptations, and handcrafted assessment functions refined over decades by human experts. The main goal of this work is to create a robust platform for position detection during chess games by combining traditional digital image processing techniques with cutting-edge object detection algorithms. The images captured during a chess game are analyzed to determine the location of each square on the board as well as the location of each piece in play; this is then repeated for each turn so that the system can follow the game in its entirety. | |
dc.publisher | Universidade Federal do Rio Grande do Norte | |
dc.publisher | Brasil | |
dc.publisher | UFRN | |
dc.publisher | Engenharia de Computação | |
dc.publisher | Departamento de Engenharia de Computação e Automação | |
dc.rights | http://creativecommons.org/licenses/by/3.0/br/ | |
dc.rights | Attribution 3.0 Brazil | |
dc.subject | Xadrez | |
dc.subject | Aprendizado de máquina | |
dc.subject | Redes neurais convolucionais | |
dc.subject | Detecção de objetos | |
dc.title | ChessPy: ferramenta para detecção inteligente de peças de xadrez | |
dc.type | bachelorThesis | |