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114
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IJCAI
1997
15 years 4 months ago
Extracting Propositions from Trained Neural Networks
This paper presents an algorithm for extract­ ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
Hiroshi Tsukimoto
166
Voted
ESANN
1997
15 years 4 months ago
Extraction of crisp logical rules using constrained backpropagation networks
Two recently developed methods for extraction of crisp logical rules from neural networks trained with backpropagation algorithm are compared. Both methods impose constraints on th...
Wlodzislaw Duch, Rafal Adamczak, Krzysztof Grabcze...
105
Voted
FSKD
2005
Springer
91views Fuzzy Logic» more  FSKD 2005»
15 years 8 months ago
Recognition of Identifiers from Shipping Container Images Using Fuzzy Binarization and Enhanced Fuzzy Neural Network
In this paper, we propose and evaluate a novel recognition algorithm for container identifiers that effectively overcomes these difficulties and recognizes identifiers from contain...
Kwang-Baek Kim
109
Voted
ENGL
2006
111views more  ENGL 2006»
15 years 2 months ago
Voice Recognition with Neural Networks, Type-2 Fuzzy Logic and Genetic Algorithms
We describe in this paper the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case of speaker recognition by analyz...
Patricia Melin, Jérica Urías, Daniel...
105
Voted
FLAIRS
2004
15 years 4 months ago
Decision Tree Extraction from Trained Neural Networks
Artificial Neural Networks (ANNs) have proved both a popular and powerful technique for pattern recognition tasks in a number of problem domains. However, the adoption of ANNs in ...
Darren Dancey, David McLean, Zuhair Bandar