Online computing of non-stationary distributions velocity fields by an accuracy controlled growing neural gas

Abstract : This paper presents a vector quantization process that can be applied online to a stream of inputs. It enables to set up and maintain a dynamical representation of the current information in the stream as a topology preserving graph of prototypical values, as well as a velocity field. The algorithm relies on the formulation of the accuracy of the quantization process, that allows for both the updating of the number of prototypes according to the stream evolution and the stabilization of the representation from which velocities can be extracted. A video processing application is presented.
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Neural Networks, Elsevier, 2014, 60, pp.203-221. 〈10.1016/j.neunet.2014.08.014〉
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Contributeur : Sébastien Van Luchene <>
Soumis le : jeudi 13 novembre 2014 - 15:55:44
Dernière modification le : jeudi 5 avril 2018 - 12:30:11

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Hervé Frezza-Buet. Online computing of non-stationary distributions velocity fields by an accuracy controlled growing neural gas. Neural Networks, Elsevier, 2014, 60, pp.203-221. 〈10.1016/j.neunet.2014.08.014〉. 〈hal-01082503〉

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