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 ...Show MoreMetadata
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.
Date of Conference: 27-30 May 2018
Date Added to IEEE Xplore: 04 May 2018
ISBN Information:
Electronic ISSN: 2379-447X