Object recognition using hierarchical temporal memory

Fabián Fallas-Moya, Francisco Torres-Rojas

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

4 Citas (Scopus)

Resumen

At this time, great effort is being directed toward developing problem-solving technology that mimic human cognitive processes. Research has been done to develop object recognition using Computer Vision for daily tasks such as secure access, traffic management, and robotic behavior. For this research, four different machine learning algorithms have been developed to overcome the computer vision problem of object recognition. Hierarchical temporal memory (HTM) is an emerging technology based on biological methods of the human cortex to learn patterns. This research applied an HTM algorithm to images (video sequences) in order to compare this technique against two others: support vector machines (SVM) and artificial neural networks (ANN). It was concluded that HTM was the most effective.

Idioma originalInglés
Título de la publicación alojadaIntelligent Computing Systems - 2nd International Symposium, ISICS 2018, Proceedings
EditoresCarlos Brito-Loeza, Arturo Espinosa-Romero
EditorialSpringer Verlag
Páginas1-14
Número de páginas14
ISBN (versión impresa)9783319762609
DOI
EstadoPublicada - 2018
Evento2nd International Symposium on Intelligent Computing Systems, ISICS 2018 - Merida, México
Duración: 21 mar 201823 mar 2018

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen820
ISSN (versión impresa)1865-0929

Conferencia

Conferencia2nd International Symposium on Intelligent Computing Systems, ISICS 2018
País/TerritorioMéxico
CiudadMerida
Período21/03/1823/03/18

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