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Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network
Seong Whan Lee
Department of Artificial Intelligence
Research output
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Contribution to journal
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Article
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peer-review
135
Citations (Scopus)
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Dive into the research topics of 'Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network'. Together they form a unique fingerprint.
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Engineering
Genetic Algorithm
100%
Recognition Rate
100%
Feature Vector
50%
Local Minimum
50%
Subnetwork
50%
Japan
50%
Telecommunication
50%
Gradient Descent
50%
Backpropagation Algorithm
50%
Computer Science
Neural Network
100%
Genetic Algorithm
50%
Recognition Rate
50%
Feature Vector
25%
Local Minimum
25%
Subnetwork
25%
Backpropagation Algorithm
25%
Trained Neural Network
25%
Gradient Descent
25%
Keyphrases
Multi-layer Cluster
100%
Offline Recognition
100%
Numerals
20%
Correct Recognition Rate
20%
Layer-cluster
20%
Network Testing
20%
Kirsch Mask
20%
Chemical Engineering
Neural Network
100%
Backpropagation
20%