IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion of handwritten word classifiers
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Lexicon-Driven Handwritten Word Recognition Using Optimal Linear Combinations of Order Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximate String Matching Using Deformed Fuzzy Automata: A Learning Experience
Fuzzy Optimization and Decision Making
Artificial Neural Networks for Document Analysis and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-line handwritten digit recognition based on trajectory and velocity modeling
Pattern Recognition Letters
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Experiments comparing neural networks trained with crisp and fuzzy desired outputs are described. A handwritten word recognition algorithm using the neural networks for character level confidence assignment was tested on images of words taken from the United States Postal Service mailstream. The fuzzy outputs were defined using a fuzzy k-nearest neighbor algorithm. The crisp networks slightly outperformed the fuzzy networks at the character level but the fuzzy networks outperformed the crisp networks at the word level. This empirical result is interpreted as an example of the principle of least commitment