FPGA implementation of an image recognition system based on tiny neural networks and on-line reconfiguration

Moreno González, Félix Antonio; Alarcón Celis, Jaime; Salvador Perea, Rubén y Riesgo Alcaide, Teresa (2008). FPGA implementation of an image recognition system based on tiny neural networks and on-line reconfiguration. En: "34th Annual Conference of the IEEE Industrial Electronics Society.IECON-2008", 10/11/2008-13/11/2008, Orlando (Florida, USA). ISBN 978-14-2441-668-4. pp. 2445-2452.

Descripción

Título: FPGA implementation of an image recognition system based on tiny neural networks and on-line reconfiguration
Autor/es:
  • Moreno González, Félix Antonio
  • Alarcón Celis, Jaime
  • Salvador Perea, Rubén
  • Riesgo Alcaide, Teresa
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 34th Annual Conference of the IEEE Industrial Electronics Society.IECON-2008
Fechas del Evento: 10/11/2008-13/11/2008
Lugar del Evento: Orlando (Florida, USA)
Título del Libro: Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE
Fecha: 2008
ISBN: 978-14-2441-668-4
Materias:
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (636kB) | Vista Previa

Resumen

Neural networks are widely used in pattern recognition, security applications and robot control. We propose a hardware architecture system; using Tiny Neural Networks (TNN) specialized in image recognition. The generic TNN architecture allows expandability by means of mapping several Basic units (layers) and dynamic reconfiguration; depending on the application specific demands. One of the most important features of Tiny Neural Networks (TNN) is their learning ability. Weight modification and architecture reconfiguration can be carried out at run time. Our system performs shape identification by the interpretation of their singularities. This is achieved by interconnecting several specialized TNN. The results of several tests, in different conditions are reported in the paper. The system detects accurately a test shape in almost all the experiments performed. The paper also contains a detailed description of the system architecture and the processing steps. In order to validate the research, the system has been implemented and was configured as a perceptron network with backpropagation learning and applied to the recognition of shapes. Simulation results show that this architecture has significant performance benefits.

Más información

ID de Registro: 3355
Identificador DC: http://oa.upm.es/3355/
Identificador OAI: oai:oa.upm.es:3355
URL Oficial: http://iecon2008.auburn.edu/index.html
Depositado por: Memoria Investigacion
Depositado el: 17 Jun 2010 08:46
Ultima Modificación: 23 Feb 2017 17:46
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM