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» Character Recognition using Spiking Neural Networks
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ISNN
2005
Springer
14 years 2 months ago
Enhanced Fuzzy Single Layer Perceptron
Abstract. In this paper, a method of improving the learning time and convergence rate is proposed to exploit the advantages of artificial neural networks and fuzzy theory to neuron...
Kwang-Baek Kim, Sungshin Kim, Young Hoon Joo, Am S...
ICDAR
2009
IEEE
14 years 3 months ago
Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...
Volkmar Frinken, Horst Bunke
IJCNN
2007
IEEE
14 years 3 months ago
Theta Neuron Networks: Robustness to Noise in Embedded Applications
- In this paper, we train a one-layer Theta Neuron Network (TNN) to perform a Braitenberg obstacle avoidance algorithm on a Khepera robot. The Theta neuron model is more biological...
Sam McKennoch, Preethi Sundaradevan, Linda G. Bush...
ICASSP
2011
IEEE
13 years 12 days ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
ICDAR
2003
IEEE
14 years 2 months ago
Generation of Hierarchical Dictionary for Stroke-order Free Kanji Handwriting Recognition Based on Substroke HMM
This paper describes a method of generating a Kanji hierarchical structured dictionary for stroke-number and stroke-order free handwriting recognition based on substroke HMM. In s...
Mitsuru Nakai, Hiroshi Shimodaira, Shigeki Sagayam...