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ESANN
2006
13 years 9 months ago
Recognition of handwritten digits using sparse codes generated by local feature extraction methods
We investigate when sparse coding of sensory inputs can improve performance in a classification task. For this purpose, we use a standard data set, the MNIST database of handwritte...
Rebecca Steinert, Martin Rehn, Anders Lansner
ENGL
2007
89views more  ENGL 2007»
13 years 7 months ago
Similarity-based Heterogeneous Neural Networks
This research introduces a general class of functions serving as generalized neuron models to be used in artiļ¬cial neural networks. They are cast in the common framework of comp...
Lluís A. Belanche Muñoz, Julio Jose ...
NC
2007
129views Neural Networks» more  NC 2007»
13 years 7 months ago
Sorting of neural spikes: When wavelet based methods outperform principal component analysis
Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is deļ...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...
ESANN
2006
13 years 9 months ago
Visual object classification by sparse convolutional neural networks
Abstract. A convolutional network architecture termed sparse convolutional neural network (SCNN) is proposed and tested on a real-world classification task (car classification). In...
Alexander Gepperth
ESANN
2003
13 years 9 months ago
Extraction of fuzzy rules from trained neural network using evolutionary algorithm
This paper presents our approach to the rule extraction problem from trained neural network. A method called REX is briefly described. REX acquires a set of fuzzy rules using an ev...
Urszula Markowska-Kaczmar, Wojciech Trelak