Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity

Ali Safa; Ilia Ocket; Andre Bourdoux; Hichem Sahli; Francky Catthoor; Georges G.E. Gielen

doi:10.1109/IJCNN55064.2022.9892362

Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity

Ali Safa, Ilia Ocket, Andre Bourdoux, Hichem Sahli, Francky Catthoor, Georges G.E. Gielen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

We present an optimization-based theory describing spiking cortical ensembles equipped with Spike-Timing-Dependent Plasticity (STDP) learning, as empirically observed in the visual cortex. Using this generic framework, we build a class of global and action-based feature descriptors for event-based cameras that we assess on the N-MNIST and the IBM DVS128 Gesture datasets. We report significant accuracy improvements compared to state-of-the-art STDP-based systems (+9.3% on N-MNIST, +7.74% on IBM DVS128 Gesture). In addition to ultra-low-power learning in neuromorphic edge devices, our work contributes towards a biologically-plausible, optimization-based theory of cortical vision.

Original language	English
Title of host publication	2022 International Joint Conference On Neural Networks (ijcnn)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	8
ISBN (Electronic)	9781728186719
DOIs	https://doi.org/10.1109/IJCNN55064.2022.9892362
Publication status	Published - 2022
Externally published	Yes
Event	2022 International Joint Conference on Neural Networks, IJCNN 2022 - Padua, Italy Duration: 18 Jul 2022 → 23 Jul 2022

Publication series

Name	Ieee International Joint Conference On Neural Networks (ijcnn)

Conference

Conference	2022 International Joint Conference on Neural Networks, IJCNN 2022
Country/Territory	Italy
City	Padua
Period	18/07/22 → 23/07/22

Keywords

Event-based camera
Spike-Timing-Dependent Plasticity
Spiking Neural Network

Access to Document

10.1109/IJCNN55064.2022.9892362

Cite this

Safa, A., Ocket, I., Bourdoux, A., Sahli, H., Catthoor, F., & Gielen, G. G. E. (2022). Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity. In 2022 International Joint Conference On Neural Networks (ijcnn) (Ieee International Joint Conference On Neural Networks (ijcnn)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN55064.2022.9892362

@inproceedings{4a8918d67cc84a3db32d4b774cd6759d,

title = "Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity",

abstract = "We present an optimization-based theory describing spiking cortical ensembles equipped with Spike-Timing-Dependent Plasticity (STDP) learning, as empirically observed in the visual cortex. Using this generic framework, we build a class of global and action-based feature descriptors for event-based cameras that we assess on the N-MNIST and the IBM DVS128 Gesture datasets. We report significant accuracy improvements compared to state-of-the-art STDP-based systems (+9.3% on N-MNIST, +7.74% on IBM DVS128 Gesture). In addition to ultra-low-power learning in neuromorphic edge devices, our work contributes towards a biologically-plausible, optimization-based theory of cortical vision.",

keywords = "Event-based camera, Spike-Timing-Dependent Plasticity, Spiking Neural Network",

author = "Ali Safa and Ilia Ocket and Andre Bourdoux and Hichem Sahli and Francky Catthoor and Gielen, {Georges G.E.}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Joint Conference on Neural Networks, IJCNN 2022 ; Conference date: 18-07-2022 Through 23-07-2022",

year = "2022",

doi = "10.1109/IJCNN55064.2022.9892362",

language = "English",

series = "Ieee International Joint Conference On Neural Networks (ijcnn)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2022 International Joint Conference On Neural Networks (ijcnn)",

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}

Safa, A, Ocket, I, Bourdoux, A, Sahli, H, Catthoor, F & Gielen, GGE 2022, Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity. in 2022 International Joint Conference On Neural Networks (ijcnn). Ieee International Joint Conference On Neural Networks (ijcnn), Institute of Electrical and Electronics Engineers Inc., 2022 International Joint Conference on Neural Networks, IJCNN 2022, Padua, Italy, 18/07/22. https://doi.org/10.1109/IJCNN55064.2022.9892362

Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity. / Safa, Ali; Ocket, Ilia; Bourdoux, Andre et al.
2022 International Joint Conference On Neural Networks (ijcnn). Institute of Electrical and Electronics Engineers Inc., 2022. (Ieee International Joint Conference On Neural Networks (ijcnn)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity

AU - Safa, Ali

AU - Ocket, Ilia

AU - Bourdoux, Andre

AU - Sahli, Hichem

AU - Catthoor, Francky

AU - Gielen, Georges G.E.

PY - 2022

Y1 - 2022

N2 - We present an optimization-based theory describing spiking cortical ensembles equipped with Spike-Timing-Dependent Plasticity (STDP) learning, as empirically observed in the visual cortex. Using this generic framework, we build a class of global and action-based feature descriptors for event-based cameras that we assess on the N-MNIST and the IBM DVS128 Gesture datasets. We report significant accuracy improvements compared to state-of-the-art STDP-based systems (+9.3% on N-MNIST, +7.74% on IBM DVS128 Gesture). In addition to ultra-low-power learning in neuromorphic edge devices, our work contributes towards a biologically-plausible, optimization-based theory of cortical vision.

AB - We present an optimization-based theory describing spiking cortical ensembles equipped with Spike-Timing-Dependent Plasticity (STDP) learning, as empirically observed in the visual cortex. Using this generic framework, we build a class of global and action-based feature descriptors for event-based cameras that we assess on the N-MNIST and the IBM DVS128 Gesture datasets. We report significant accuracy improvements compared to state-of-the-art STDP-based systems (+9.3% on N-MNIST, +7.74% on IBM DVS128 Gesture). In addition to ultra-low-power learning in neuromorphic edge devices, our work contributes towards a biologically-plausible, optimization-based theory of cortical vision.

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KW - Spiking Neural Network

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M3 - Conference contribution

AN - SCOPUS:85140713036

T3 - Ieee International Joint Conference On Neural Networks (ijcnn)

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Safa A, Ocket I, Bourdoux A, Sahli H, Catthoor F, Gielen GGE. Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity. In 2022 International Joint Conference On Neural Networks (ijcnn). Institute of Electrical and Electronics Engineers Inc. 2022. (Ieee International Joint Conference On Neural Networks (ijcnn)). doi: 10.1109/IJCNN55064.2022.9892362

Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity

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