Developing a New CNN Technique for Arabic Handwritten Digits Recognition
Hamdy Amin Morsy
Hamdy Amin Morsy, Department of Electronics and Communications Engineering, Faculty of Engineering at Helwan University, Cairo, Egypt.
Manuscript received on 01 August 2020 | Revised Manuscript received on 05 August 2020 | Manuscript Accepted on 15 September 2020 | Manuscript published on 30 September 2020 | PP: 520-524 | Volume-9 Issue-3, September 2020 | Retrieval Number: 100.1/ijrte.C4588099320 | DOI: 10.35940/ijrte.C4588.099320
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Abstract: Convolutional Neural Networks (CNN) have many applications in object recognition such as character and digit recognition. Few researches are performed on Arabic handwritten digits recognition. In this research, we will develop a new algorithm to utilize the convolutional neural networks with sigmoid function (σ-CNN) to recognize Arabic handwritten digits recognition. The performance of this method provides minimum cost functions with maximum testing accuracy results in compared to other existing techniques.
Keywords: Machine Learning, Neural Networks, Image Processing, Natural Language Processing.