Título: Position Estimation Of UAV By Image Processing With Neural Networks
Autores: Goltz, G. A. M.; Shiguemori, E. H.; Velho, Haroldo F. De Campos
Resumo: This paper presents a study of three artificial neural networks with supervised training and different architectures: network with radial basis function, multilayer perceptron and cellular neural network. These networks were applied to edge detection in aerial and satellite images, for later correlation calculation in spatial domain between these images to simulate the estimation of the geographical position of a unmanned aerial vehicle – UAV. The neural networks results were compared with Sobel and Canny operators.
Palavras-chave: Artificial Neural Networks; Image Processing; Air Navigation by Images
Código DOI: 10.21528/CBIC2011-03.6
Artigo em pdf: st_03.6.pdf
Arquivo BibTex: st_03.6.bib