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21 results for “Handwritten Recognition”
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Research ArticleOpen accessIn the abstractImproving the Eastern Arabic Hand Written Digits Recognition Using Deep LearningHamdy Morsy, Hashim M. Hasanien et al.Convolutional neural networks CNNs or simply deep learning was designed for the challenging of object recognition such as digits, characters and even objects that can be classified. The deep convolutional networks are designed to be trained through using a large dataset of the classes. The degree of complexity of recognizing handwritten digits are different from person to person and even … …Journal of Computer Science, Vol. 21, Issue 6 · 27 May 2025 · 4,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Transformed and Geometrically Distorted Images using Convolutional Neural NetworkSanad Aburass, Ammar Huneiti, Mohammad Belal Al-ZoubiConvolutionalNeural Network is a deep learning method that is used in many image-relatedapplications, such as image recognition and classification, it has achievedgreat performance in these fields, but it still suffers from some shortcomings.One of these shortcomings is not being able to be invariant to the input datadue to some image transformations like translation, rotation, scaling, andgeometric distortions such as skewness, … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,138 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Implementation of Stochastic Computing Based Deep Neural Network on Low Cost Hardware with Saturation ArithmeticSunny Bodiwala, Nirali NanavatiThis study presents an efficient and rapid implementation of Stochastic Computing (SC) based Deep Neural Network (DNN) on a low-cost hardware platform. The proposed technique uses bipolar signal encoding in stochastic computing which relatively gives low hardware footprint compared to binary computing. Thereinafter, stochastic max function is presented and subsequently used to approximate the hyperbolic tangent activation function in SC. … …Journal of Computer Science, Vol. 16, Issue 11 · 17 Nov 2020 · 6,875 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Neural Network for Recognizing Gestural Hindi DigitsNidal Fawzi Shilbayeh, Mohammad Mahmmoud Alwakeel, Maisa Mohy NaserHandwritten Hindi digit recognition plays an important role in eastern Arab countries especially in the courtesy amounts of Arab bank checks, recognizing numbers in car plates, or in postal code for mail sorting. In our study, we proposed an efficient Hindi Digit Recognition System drawn by the mouse and developed using Multilayer Perceptron Neural Network (MLP) with backpropagation. The system … …American Journal of Applied Sciences, Vol. 10, Issue 9 · 24 Aug 2013 · 6,882 accessesView PDFCite
Research ArticleOpen accessIn the abstractHandwritten Characters Extraction from Form Based on Line Shape CharacteristicsAli Qusay Al-Faris, Dzulkifli Mohamad, Umi Kalthum Ngah, Nor Ashidi Mat IsaProblem statement: Data entry form is a convenient and successful tool for information collection by filling in the sheets using pen and handwriting. One of the most important fields in these forms is the data filled boxes. Extracting the handwriting from the data entry forms is important for many purposes such as in documenting and archiving. The extraction process is … …Journal of Computer Science, Vol. 7, Issue 12 · 15 Oct 2011 · 7,934 accessesView PDFCite
Research ArticleOpen accessIn the abstractDigital Recognition using Neural NetworkSaleh Ali K. Al-Omari, Putra Sumari, Sadik A. Al-Taweel, Anas J.A. HusainProblem statement: Handwriting number recognition is a challenging problem researchers had been research into this area for so long especially in the recent years. In our study there are many fields concern with numbers, for example, checks in banks or recognizing numbers in car plates, the subject of digit recognition appears. A system for recognizing isolated digits may be as … …Journal of Computer Science, Vol. 5, Issue 6 · 30 Jun 2009 · 7,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Moment Features Extraction for Recognizing Handwritten Arabic LettersGheith Abandah, Nasser AnssariProblem statement: Offline recognition of handwritten Arabic text awaits accurate recognition solutions. Most of the Arabic letters have secondary components that are important in recognizing these letters. However these components have large writing variations. We targeted enhancing the feature extraction stage in recognizing handwritten Arabic text. Approach: In this study, we proposed a novel feature extraction approach of handwritten Arabic … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,495 accessesView PDFCite
Research ArticleOpen accessIn the abstractBack Propagation Neural Network Arabic Characters Classification Module Utilizing Microsoft WordA. A. HamzaProblem statement: Arabic character recognition has been one of the last major languages to receive attention. This may be attributed to the inherent complexity of both printed and handwritten Arabic characters. The objectives of this study were to: (i) summarize the main characteristics of Arabic language writing style. (ii) suggest a neural network recognition circuit. Approach: A Neural network with … …Journal of Computer Science, Vol. 4, Issue 9 · 30 Sep 2008 · 7,831 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomatic Arabic Hand Written Text Recognition SystemIsmael Ahmad JannoudDespite of the decent development of the pattern recognition science applications in the last decade of the twentieth century and this century, text recognition remains one of the most important problems in pattern recognition. To the best of our knowledge, little work has been done in the area of Arabic text recognition compared with those for Latin, Chins and Japanese … …American Journal of Applied Sciences, Vol. 4, Issue 11 · 30 Nov 2007 · 7,315 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Comparison of Different Image Sizes for Recognizing Unconstrained Handwritten Tamil Characters using SVMN. Shanthi, K. DuraiswamyThis study describes a system for recognizing offline handwritten Tamil characters using Support Vector Machine (SVM). Data samples are collected from different writers on A4 sized documents. They are scanned using a flat bed scanner at a resolution of 300 dpi and stored as grey scale images. Various preprocessing operations are performed on the digitized image to enhance the quality … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 7,008 accessesView PDFCite