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Evaluating SPAN incremental learning for handwritten digit recognition


Mohemmed, A; Guoyu, L; Kasabov, N (2012). Evaluating SPAN incremental learning for handwritten digit recognition. In: 19th International Conference on Neural Information Processing (ICONIP2012) , Doha, Qatar, 12 November 2012 - 15 November 2012, 670-677.

Abstract

In a previous work [12, 11], the authors proposed SPAN: a learning algorithm based on temporal coding for Spiking Neural Network (SNN). The algorithm trains a neuron to associate target spike patterns to input spatio-temporal spike patterns. In this paper we present the details of experiment to evaluate the feasibility of SPAN learning on a real-world dataset: classifying images of handwritten digits. As spike encoding is an important issue in using SNN for practical applications, we discuss few methods for image conversion to spike patterns. The experiment yields encouraging results to consider the SPAN learning for practical temporal pattern recognition applications.

Abstract

In a previous work [12, 11], the authors proposed SPAN: a learning algorithm based on temporal coding for Spiking Neural Network (SNN). The algorithm trains a neuron to associate target spike patterns to input spatio-temporal spike patterns. In this paper we present the details of experiment to evaluate the feasibility of SPAN learning on a real-world dataset: classifying images of handwritten digits. As spike encoding is an important issue in using SNN for practical applications, we discuss few methods for image conversion to spike patterns. The experiment yields encouraging results to consider the SPAN learning for practical temporal pattern recognition applications.

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Additional indexing

Item Type:Conference or Workshop Item (Speech), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:15 November 2012
Deposited On:28 Feb 2013 08:21
Last Modified:03 Aug 2017 00:45
Publisher:Springer
Series Name:Lecture Notes in Computer Science
Number:7665
Number of Pages:8
ISSN:0302-9743
ISBN:978-3-642-34486-2
Additional Information:The original publication is available at www.springerlink.com
Publisher DOI:https://doi.org/10.1007/978-3-642-34487-9_81

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