Handwritten Digit Recognition Using Convolutional Neural Networks
Recently handwritten digit recognition becomes vital scope and it is appealing many researchers because of its using in variety of machine learning and computer vision applications. However, there are deficient works accomplished on Arabic pattern digits because Arabic digits are more challenging than English patterns. Hence, the lacking research of using Arabic digits endeavours us to dig deeper by creating our challenge Arabic Handwritten Digits which consists of more than 45,000 samples. As a challenging dataset is used for evaluation, a robust deep convolutional neural network is used for classification and superior results are achieved.