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. hoda database, which includes 80000 p...

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. Hoda database, which includes 80000 P...

A new method for recognition of isolated handwritten Arabic/Persian digits is presented. This method is based on Support Vector Machines (SVMs), and a new approach of feature extraction. Each digit is considered from four different views, and from each view 16 features are extracted and combined to obtain 64 features. Using these features, multiple SVM classifiers are trained to separate differ...

In pursuit of Persian handwritten digit recognition, many machine learning techniques have been utilized. Mixture of experts (MOE) is one of the most popular and interesting combining methods which has great potential to improve performance in machine learning. In MOE, during a competitive learning process, the gating networks supervise dividing input space between experts and experts obtain sp...

This paper aims to improve the feature extraction of Persian handwritten number recognition systems. In this paper, we introduced nine new features for detection and recognition of Persian handwritten digits using the technique of finding the smallest enclosing disc in computational geometry. All these features are based on the geometry form of numbers and are much better than the features in t...

In spite of various applications digit, letter and word recognition, only a few studies have dealt with Persian scripts. this paper, deep neural networks are utilized through different DenseNet Xception architectures, being further boosted by means data augmentation test time augmentation. Dividing the datasets to training, validation sets, utilizing k-fold cross-validation, comparison proposed...