Persian Handwritten Digit Recognition Using Particle Swarm Probabilistic Neural Network

نویسندگان
Taghipour-GorjiKolaie, Mehran ID 1
Miri, Ismaeil ID 2
Razavi, Seyyed-Mohammad ID 3
Sadri, Javad ID 4

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چکیده

Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. ...

کلیدواژه‌ها
Probabilistic Neural Network (PNN), Classification, Persian handwritten digit recognition, Particle swarm optimization, clustering, K-means.