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» Interpretation of Trained Neural Networks by Rule Extraction
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AIA
2006
15 years 2 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»
15 years 1 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 6 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 3 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 5 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&...