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» Interpretation of Trained Neural Networks by Rule Extraction
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AIA
2006
15 years 1 months ago
Recurrent and Concurrent Neural Networks for Objects Recognition
A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task....
Federico Cecconi, Marco Campenní
EOR
2007
101views more  EOR 2007»
14 years 11 months ago
Comprehensible credit scoring models using rule extraction from support vector machines
In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformat...
David Martens, Bart Baesens, Tony Van Gestel, Jan ...
ICDAR
2003
IEEE
15 years 5 months ago
A Contour Code Feature Based Segmentation For Handwriting Recognition
The purpose of this paper is to present a novel contour code feature in conjunction with a rule based segmentation for cursive handwriting recognition. A heuristic segmentation al...
Brijesh Verma
ANNPR
2006
Springer
15 years 1 months ago
A Convolutional Neural Network Tolerant of Synaptic Faults for Low-Power Analog Hardware
Abstract. Recently, the authors described a training method for a convolutional neural network of threshold neurons. Hidden layers are trained by by clustering, in a feed-forward m...
Johannes Fieres, Karlheinz Meier, Johannes Schemme...
ICANN
2001
Springer
15 years 4 months ago
Extracting Slow Subspaces from Natural Videos Leads to Complex Cells
Natural videos obtained from a camera mounted on a cat’s head are used as stimuli for a network of subspace energy detectors. The network is trained by gradient ascent on an obje...
Christoph Kayser, Wolfgang Einhäuser, Olaf D&...