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» Character Recognition using Spiking Neural Networks
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ISNN
2005
Springer
15 years 5 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
15 years 6 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
15 years 6 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
14 years 3 months 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
15 years 5 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...