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23 articles for “handwritten”
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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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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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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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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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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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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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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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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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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 Line Segmentation for Kannada Language Using Enhanced Horizantol Projection Profile Method
Abstract: Handwritten character image is taken as dataset for this method. Segmentation is crucial in the Human Character Recognition System for extracting text lines, words, and characters from handwritten Kannada documents. In the proposed system, segmenting text lines, word, characters are done based on enhanced horizantol projection profile approach. The algorithm will be used for finding the height and width of the entire handwritten word The horizontal projection profile approach is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 2, 2023 · pp. 1–8 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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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
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AI Chatbot for Expressing Visual Content
Abstract: Recently, the artificial intelligence (AI) chatbot for expressing visual content has shown remarkable multi-modal capabilities. It can recognize funny features in photos and create webpages straight from handwritten text. These characteristics are uncommon in earlier vision language models. We think the use of a more sophisticated large language model (LLM) is the main factor behind vision verbalizer's superior multi-modal generating capabilities. We introduce vision verbalizer, which employs a single projection …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 11–19 Read article
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Approach to Perform Sentimental Analysis Using Graphology
Abstract: Handwriting is one of the means to foretell the actions of a person by analyzing the shapes, sizes, altitude, convention and stress of the letters. In a rapid world where people are growing with the new technologies every day, sentimental analysis has also become a key tool to analyze the handwritten data, expressing the behavior or the etiquette of a people. We also have tried to perform analysis on the …
Published in Journal of Experimental & Applied Mechanics · Vol. 11, Issue 1, 2020 · pp. 6–10 Read article
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Personality and Behavior Identification Based on Handwriting Analysis
Abstract: Graphing is the process of identifying, evaluating, and understanding a person's personality traits through handwritten patterns. The accuracy of handwriting analysis depends on the skill of the analyst, it is expensive and prone to errors. The proposed approach is therefore focused on building a system that can predict personality traits with the help of machine learning without human intervention. In this project, 657 authors' handwritten samples were taken as datasets. …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 1, 2022 · pp. 42–54 Read article
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Advanced Signature Verification Techniques: A Review
Abstract: There are various authentication techniques existing in these days to verify the originality of the owner’s identification, based on new technology and human computer interfaces like voice recognition and image processing like face detection methods to avoid the frauds. The popular noncomputer vision-based techniques like fingerprint authentication and passwords are most popular now, but what about the traditional method of the authenticity i.e., handwritten signature. In this era of technology …
Published in Journal Of Network security · Vol. 10, Issue 1, 2022 · pp. 1–6 Read article
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AI Evaluator – Automated Examination Evaluation
Abstract: An AI system for automated exam grading is proposed. It tackles inefficiencies in human evaluation. The system uses TrOCR for accurate handwritten text recognition and a GPT model trained on graded responses for evaluation. This approach offers efficiency and reduced bias, but challenges remain. Evaluating open-ended questions and ensuring explainability require further development. It starts by looking at how AI technologies, such as machine learning, deep learning, and natural language …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–9 Read article
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Digital Resurrection: Restoring Fragile Documents with OCR
Abstract: In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 29–35 Read article
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AI-Driven Exam Evaluation Systems: Challenges, Innovations, and Future Directions
Abstract: A proposed AI system is used to grade exams automatically. It addresses inefficiencies in human assessment. A GPT model trained on graded replies is used for evaluation, and TrOCR is used for precise handwritten text recognition. Efficiency and less bias are provided by this method, although there are still issues. More work is needed to assess open-ended questions and make sure they are understandable. To automate many aspects of exam …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 7–13 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article