Live Demonstration: Image Classification Using Bio-inspired Spiking Neural Networks

Shruti R. Kulkarni, John M. Alexiades, Bipin Rajendran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a live demonstration of an image classification system using bio-inspired Spiking Neural Networks. Our network is three-layered and is trained with the images from the MNIST database, achieving an accuracy of 98.06%. Synapses connecting the output layer neurons obey the spike based weight-adaptation rule using the supervised learning algorithm called NormAD. This network, implemented on a graphical processing unit (GPU), is used to classify digits drawn by users on a touch-screen interface in real-time. The spike propagation maps generated and displayed by the platform reveal key insights about information processing mechanisms of the brain.

Original languageEnglish (US)
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538648810
DOIs
StatePublished - Apr 26 2018
Event2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
Duration: May 27 2018May 30 2018

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2018-May
ISSN (Print)0271-4310

Other

Other2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
CountryItaly
CityFlorence
Period5/27/185/30/18

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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