Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn 2015-July, Issue , 2015, Pages 1901-

  Stromatias, Evangelos ^a   Neil, Daniel ^c   Galluppi, Francesco ^b   Pfeiffer, Michael ^c   Liu, Shih Chii ^c   Furber, Steve ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b INSTITUT DE LA VISION   (France)

^c UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Associated Track 8.1: Neural Networks and Systems; Spiking Neural Network circuits and systems

Indexed keywords

BAYESIAN NETWORKS; BIOMIMETICS; CHARACTER RECOGNITION; COMPUTER ARCHITECTURE;

BIOLOGICALLY INSPIRED; CIRCUITS AND SYSTEMS; DEEP BELIEF NETWORKS; HANDWRITTEN DIGIT RECOGNITION; MANY-CORE ARCHITECTURE; REAL TIME; RUNNING-IN;

NEURAL NETWORKS;

EID: 84946230589     PISSN: 02714310     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISCAS.2015.7169034     Document Type: Conference Paper

References (3)

1. P. O'Connor, D. Neil, S.-C. Liu, T. Delbruck, and M. Pfeiffer, "Realtime classification and sensor fusion with a spiking deep belief network," Frontiers in Neuroscience, vol. 7, no. 178, 2013.
2. D. Neil and S.-C. Liu, "Minitaur, an event-driven FPGA-based spiking network accelerator," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. PP, no. 99, pp. 1-1, 2014.
3. S. Furber, F. Galluppi, S. Temple, and L. Plana, "The SpiNNaker project," Proceedings of the IEEE, vol. 102, no. 5, pp. 652-665, May 2014.