An Effective Deep Learning Approach for Improving Off-Line Arabic Handwritten Character Recognition
Developing systems in computer vision domain persuades researchers in many applications. The main goal in computer vision applications is to enable the computers to imitate the humans in their vision system. Various systems developed for classifying and recognizing different type of images. This paper introduces an effective approach towards designing a system for recognizing an isolated handwritten Arabic character based on deep learning technique. The deep learning based on convolutional neural network (CNNs plays an important role in every single application of computer vision domain. A CNN model is developed and trained with Arabic handwritten characters in offline mode. Testing the proposed system yields to an excellent recognition results in both training and testing.