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Submodular neural network is better than modular neural network and support vector machines for personal verification
By: Eguchi, H.; Hirahara, M.; Nagano, T.;
2003 / IEEE / 0-7803-7898-9
Description
This item was taken from the IEEE Conference ' Submodular neural network is better than modular neural network and support vector machines for personal verification ' A sub-modular neural network (SMNN) proposed a few years ago is compared with the usual modular neural network (MNN) and support vector machines (SVM) in terms of pattern recognition performance. Some computer simulation results showed that SMNN was much superior to MNN and SVM as for rejection rates of patterns in unlearned classes under the condition that they gave almost the same recognition rates for patterns in learned classes. These results strongly suggest that SMNN is more suitable for personal verification systems than the other two as such systems require high rejection rate for patterns in unlearned classes.
Related Topics
Neural Nets
Svm
Submodular Neural Network
Modular Neural Network
Support Vector Machines
Personal Verification System
Pattern Recognition Performance
Recognition Rate
Unlearned Class Patterns
Learned Class Patterns
Biometric Cues
Neural Networks
Support Vector Machines
Multi-layer Neural Network
Pattern Recognition
Support Vector Machine Classification
Neurons
Computer Simulation
Samarium
Biometrics
Support Vector Machines
Pattern Recognition
Biometrics (access Control)
Engineering
Rejection Rate