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» Character Recognition using Spiking Neural Networks
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NCI
2004
132views Neural Networks» more  NCI 2004»
13 years 8 months ago
A comparison between spiking and differentiable recurrent neural networks on spoken digit recognition
In this paper we demonstrate that Long Short-Term Memory (LSTM) is a differentiable recurrent neural net (RNN) capable of robustly categorizing timewarped speech data. We measure ...
Alex Graves, Nicole Beringer, Jürgen Schmidhu...
ICDAR
2011
IEEE
12 years 7 months ago
BLSTM Neural Network Based Word Retrieval for Hindi Documents
—Retrieval from Hindi document image collections is a challenging task. This is partly due to the complexity of the script, which has more than 800 unique ligatures. In addition,...
Raman Jain, Volkmar Frinken, C. V. Jawahar, Raghav...
SIAMADS
2010
145views more  SIAMADS 2010»
13 years 2 months ago
Propagation of Spike Sequences in Neural Networks
Precise spatiotemporal sequences of action potentials are observed in many brain areas and are thought to be involved in the neural processing of sensory stimuli. Here, we examine ...
Arnaud Tonnelier
ICDAR
1999
IEEE
13 years 11 months ago
Multifont Classification using Typographical Attributes
This paper introduces a multifont classification scheme to help recognition of multifont and multisize characters. It uses typographical attributes such as ascenders, descenders a...
Min-Chul Jung, Yong-Chul Shin, Sargur N. Srihari
ESANN
2008
13 years 9 months ago
An FPGA-based model suitable for evolution and development of spiking neural networks
We propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs using a piecewise linear approximation of the Quadratic Integrate...
Hooman Shayani, Peter J. Bentley, Andrew M. Tyrrel...