Abstract
In this work we have used directional features extracted from Gabor wavelet responses to compare different auto-organised networks in order to extract perceptual primitives without taking into account the kind of images to analyse. This is an adequate problem to prove the performance of these models because of the high dimensionality of the input space. Three different models have been analysed: self-organised maps, growing-cell structures and growing neural gas. Results have proved that growing-cell structures generalise better all directional perceptual primitives we are searching for, and they do not provide very noisy images.
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© 2001 Springer-Verlag Berlin Heidelberg
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Penas, M., Carreira, M.J., Penedo, M.G. (2001). Autoorganised Structures for Extraction of Perceptual Primitives. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_76
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DOI: https://doi.org/10.1007/3-540-45723-2_76
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