Ponencia
Foveal-pit inspired filtering of DVS spike response
Autor/es | Gupta, Shriya T.P
Linares Serrano, Pablo Sen Bhattacharya, Basabdatta Serrano Gotarredona, María Teresa ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Departamento | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores |
Fecha de publicación | 2021 |
Fecha de depósito | 2024-02-15 |
Publicado en |
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ISBN/ISSN | 978-166541268-1 |
Resumen | In this paper, we present results of processing
Dynamic Vision Sensor (DVS) recordings of visual patterns with a
retinal model based on foveal-pit inspired Difference of Gaussian
(DoG) filters. A DVS sensor was stimulated ... In this paper, we present results of processing Dynamic Vision Sensor (DVS) recordings of visual patterns with a retinal model based on foveal-pit inspired Difference of Gaussian (DoG) filters. A DVS sensor was stimulated with varying number of vertical white and black bars of different spatial frequencies moving horizontally at a constant velocity. The output spikes generated by the DVS sensor were applied as input to a set of DoG filters inspired by the receptive field structure of the primate visual pathway. In particular, these filters mimic the receptive fields of the midget and parasol ganglion cells (spiking neurons of the retina) that sub-serve the photo-receptors of the foveal- pit. The features extracted with the foveal-pit model are used for further classification using a spiking convolutional neural network trained with a backpropagation variant adapted for spiking neural networks. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Consejo Superior de Investigaciones Científicas (CSIC) Science and Engineering Research Board Comisión Europea |
Identificador del proyecto | PCI2019-111826-2
![]() CRG/2019/003534 ![]() PID2019-105556GB-C31 ![]() 2018-50E008 AVE project ![]() |
Cita | Gupta, S.T.P., Linares Serrano, P., Sen Bhattacharya, B. y Serrano Gotarredona, T. (2021). Foveal-pit inspired filtering of DVS spike response. En 55th Annual Conference on Information Sciences and Systems, CISS 2021 (168475), Baltimore, 24 - 26 Marzo: Institute of Electrical and Electronics Engineers Inc. (IEEE). |
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