@inproceedings{e736e2c311d641ff87d368e0c8347d8a,
title = "A SOM-based fuzzy system and its application in handwritten digit recognition",
abstract = "The paper presents a neuro-fuzzy system by using Kohonen's self-organizing feature map algorithm, not only for its vector quantization feature, but also for its topological property. This property prevents the proposed neuro-fuzzy system from suffering from a drawback like any of the conventional clustering algorithm based fuzzy systems, i.e. the optimal number of clusters or some kind of similarity threshold must be predetermined. Associated with the self-organizing feature map based fuzzy system is a hybrid learning algorithm, which is for initial parameter setting and fine-tuning the parameters of the system. Application of the proposed fuzzy systems in optical handwritten digit recognition is reported. High recognition rates can be achieved.",
keywords = "fuzzy systems, neural networks, optical character recognition, self-organizing feature map",
author = "Su, {Mu Chun} and E. Lai and Tew, {Chee Yuen}",
note = "Publisher Copyright: {\textcopyright} 2000 IEEE.; null ; Conference date: 11-12-2000 Through 13-12-2000",
year = "2000",
doi = "10.1109/MMSE.2000.897219",
language = "???core.languages.en_GB???",
series = "Proceedings - International Symposium on Multimedia Software Engineering",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "253--258",
booktitle = "Proceedings - International Symposium on Multimedia Software Engineering",
}