2026-09-18T01:25:38Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1351152025-05-29T07:24:10Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134811
Gestión del Repositorio Documental de la Universidad de Salamanca
author
Corchado RodrÃguez, Emilio Santiago
author
Charles, Darryl
author
Fyfe, Colin
2017-09-06T09:16:41Z
2017-09-06T09:16:41Z
2001-04
ESANN'2001 proceedings - European Symposium on Artificial Neural Networks. pp. 397-402.
2-930307-01-3
https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2001-33.pdf
We investigate the use of an unsupervised artificial neural network to form a sparse representation of the underlying causes in a data set. By using fixed lateral connections that are derived from the Rectified Generalised Gaussian distribution, we form a network that is capable of identifying multiple cause structure in visual data and grouping similar causes together on the output response of the network. We show that the network may be used to form local spatiotemporal filters in response to real images contained in video data.
en
Attribution-NonCommercial-NoDerivs 3.0 Unported
Computer Science
Rectified Gaussian Distributions and the Formation of Local Filters From Video Data
info:eu-repo/semantics/conferenceObject
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