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33 articles for “Handwriting recognition”
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Advancements in Handwriting Recognition: A Deep Learning Approach
Abstract: This article provides detailed information about handwriting text recognition. Some human characteristics are unique to the individual. Writing is one of the scientifically proven habits that is different for everyone. Handwriting Text Recognition (HTR) is responsible for identifying written characters and converting them into digital text. HTR is an intensively researched area, but improvements can still be made in accuracy and efficiency. Digitization of manuscripts is very useful in today's …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Hybrid HMM/ANN Models for Improving Offline Handwritten Text Recognition
Abstract: AbstractIn this approach, it proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing the unconstrained offline handwritten texts. Handwritten image normalization from a scanned image includes several steps, usually it begin with image cleaning, page skew correction, and line detection. For handwritten text line image several pre-processing steps to reduce variation in writing style are performed like slope and slant removal and character size …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 16–23 Read article
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Historical Kannada Handwritten Character Recognition using K-Nearest Neighbour Technique
Abstract: AbstractMost of the historical Kannada handwritten documents are preserved in the manuscript preservation center and archaeological department, and these documents are generally degraded in nature and it is very difficult to read and understand the contents in it. Hence, it is very much essential to digitize the historical Kannada handwritten document and recognize its originality of dynasty. The main objective of this paper is to digitize and recognize the historical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 23–29 Read article
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A Study on Offline Handwritten Character Recognition (OHCR) of Devanagari Script
Abstract: Handwritten Character Recognition (HCR) has been an interesting and challenging area for the researchers and plays an important role in the modern world. Devanagari script contains many Indian languages such as Hindi, Marathi, Rajasthani. All these languages are based on Devanagari script. In this paper, we give an overview on different classifiers (to get the idea of recognition results) and provide new benchmark for future research from the existing systems, …
Published in Journal of Open Source Developments · Vol. 1, Issue 2, 2014 · pp. 11–14 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
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Identification of Handwritten Digits using Machine Learning
Abstract: Handwritten Digit Recognition is one of the practical issues in sample recognition applications. The task for handwritten recognition has been difficult due to various variations in written styles. The capacity to create an effective algorithm that can detect handwritten numbers given by users via a scanner, tablet, and other digital devices is at the core of the issue. Artificial intelligence is used in machine learning, which automatically corrects errors based …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 19–26 Read article
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Recognition of Unconstrained Handwritten Digits Using Feedforward MLP and Projection Profile
Abstract: AbstractThis paper presents a new approach to off-line handwritten numeral recognition using feedforward MLP and projection profile. Different writers have variations in their handwriting since each writer possesses own writing speed, own styles, sizes or positions for numeral or text. Recognition of handwritten numerals poses serious problems because of high variability in numeral shapes written by individuals. The performance of character recognition system depends heavily on what kind of features …
Published in Journal of Communication Engineering & Systems · Vol. 5, Issue 2, 2015 · pp. 15–20 Read article
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Handwritten Digit Recognition Using Logistic Regression, SVM, KNN and CNN Algorithms
Abstract: The style of handwriting varies from person to person. Handwritten numbers are not always the same size, orientation and width. To develop a system to understand this, the machine recognizes handwritten digit images and classifies them into 10 digits (from 0 to 9). The recognition of handwritten digits is a technology which is used for the automatic recognizing and detecting handwritten digital data through various deep lerning and machine learningmodels. …
Published in Journal of Operating Systems Development & Trends · Vol. 9, Issue 2, 2022 · pp. 20–28 Read article
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Offline Handwritten Sanskrit Character Recognition System
Abstract: Despite technological improvements, computers still lag behind in language recognition. The majority of character recognition systems are incapable of reading cracked documents or handwritten characters or words. Sanskrit, an alphabetic script, is spoken by more than 100 million people worldwide. This study is about converting scanned handwriting images into text. This contains the steps below. The scanned image is initially segmented using a spatial space detection approach, after which the …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 32–37 Read article
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Handwritten Telugu Character Recognition Using Machine Learning – A Detailed Survey
Abstract: Telugu language is largest member of the Dravidian language family. Primarily spoken in south-eastern India. The handwritten character recognition of Telugu has wide range of applications in healthcare, administrations, education, Palaeography. However, the Telugu script is very different from English. This makes the use of CNN to recognize the Telugu characters.Converted into several data formats for use in a variety of documents, agreements, and private files. Electronic data uses less …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 2, 2023 · pp. 32–39 Read article
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Handwritten Sanskrit Word Recognition: A Deep Learning Approach Using AlexNet
Abstract: Handwritten Sanskrit word recognition poses significant challenges due to the intricate structure of the script and the considerable variations in handwriting across individuals. To address these challenges, this research introduces a novel methodology employing transfer learning with the AlexNet convolutional neural network. The study utilized two distinct datasets: a specifically curated Sanskrit word image dataset containing 2616 samples, alongside a broader Devanagari character dataset used for validation purposes. The established …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Bangla Handwritten Digit and Basic Letter Recognition Using Machine Learning Techniques
Abstract: AbstractThe usage of computer is increasing day by day in Bangladesh, so the use of Bangla is increasing in computer. Furthermore, the use of Bangla handwritten character is also increasing in many computer applications. There exist many techniques for recognition of handwritten character. From the studies we see that machine learning techniques are better techniques for recognition of handwritten character than others. A necessary prerequisite for measuring the performance of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 1–15 Read article
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Handwritten English Alphabet Recognition Using Convolutional Neural Network
Abstract: This research paper presents an approach for English alphabet recognition using machine learning. The proposed system utilizes a convolutional neural network (CNN) to identify individual characters within an input image. The dataset used in this research consists of a large collection of handwritten alphabet images, sourced from Kaggle's A-Z Handwritten Alphabets dataset in CSV (comma-separated values) format, which were preprocessed and augmented to improve the model's accuracy. We trained and …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 17–25 Read article
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Online Handwritten Kannada Character Recognition and Translation to English
Abstract: Abstract—The objective of the paper is to develop a technique that can efficiently recognize hand-written characters of Kannada language and then translate the same to English language. Online recognition refers to the processing of the characters as and when it is written on digitizer and recognizes the class which it belongs to. The iball 5540U Pen Tablet is used to collect the handwritten character samples and to build the database. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 2, 2019 · pp. 37–53 Read article
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CNN-BILSTM Architectures for Handwritten Signature Verification: Insights and Innovations
Abstract: Verifying handwritten signatures is essential for identity authentication to guard against fraud and guarantee security across a range of platforms. The approaches and developments in handwritten signature verification are examined in this review, with an emphasis on both offline and online techniques. While online methods use dynamic information like stroke order and speed, collected by specialized devices, offline verification uses scanned photographs of signatures. Even if technology is moving toward …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 43–50 Read article
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Optical/Handwritten Data Recognition
Abstract: For many years, optical character recognition (OCR) has been a hot topic. It's the process of breaking down a document image into its individual characters. Despite decades of intensive research, producing OCR with human-like skills is still a work in progress. The industries have long used localization and recognition of written characters for a number of applications. When working in a sterile environment, such as scanners or static settings, most …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 2, 2021 · pp. 22–31 Read article
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Hand-Writing Recognition Using Structural, Statistical Features
Abstract: One of the very crucial challenges in pattern recognition operations is handwriting recognition, often known as handwritten number recognition. The processing of bank checks, the sorting of postal mail, the entry of data into forms, etc. are all procedures involving number recognition. The ability to create an efficient algorithm that can retrieve handwritten integers submitted by drug users via a scanner, tablet, and other digital gadgets is at the core …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 1, 2023 · pp. 8–14 Read article
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Text Recognition and Detection of Handwritten Reports Through Image Processing
Abstract: Nowadays, the biggest problem we are facing is text detection from the scene images, handwritten documents, and various other images at different resolutions. To overcome such problems, we are using artificial intelligence tools and techniques which make use of neural networks to detect the text from the images. In this work, we proposed new solutions to this problem by introducing Artificial Neural Network Techniques which have proven best for text …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 9, Issue 3, 2022 · pp. 1–6 Read article
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Digital Entry of Bank Related Slips Using Character Recognition
Abstract: Standing in long queues in bank for small work like depositing the money is very frustrating and also wastes a lot of time. The bank employee handles all the work such as making the entry of money deposited or credit from the account manually by typing information such as account number, amount, etc. and due this creates long queues in banks for such small tasks. Thus, we have come up …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 30–35 Read article