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OCR-MRD: performance analysis of different optical character recognition engines for medical report digitization
In the modern era, the necessity of digitization is increasing in a rapid manner day-to-day. The healthcare industries are working towards operating...
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Algorithms of the Tiger and CuneiForm Optical Character Recognition Software
AbstractIn this paper, the optical character recognition (OCR) software is considered. The algorithmic solutions of two of the world’s best OCR...
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A Review of Optical Character Recognition (OCR) Techniques on Bengali Scripts
The technique of transforming analogue documents into digital documents using document images is known as Optical Character Recognition (OCR). Since...
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Ancient Kannada Handwritten Character Recognition from Palm Leaf Manuscripts Using PyTesseract-OCR Technique
Ancient Kannada character recognition is a strenuous task since the Kannada language evolved over various decades, expanding and diversifying the...
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Smart Checkpoint Management System for Automatic Number Plate Recognition in Bhutan Vehicles Using OCR Technique
Smart Checkpoint Management System (SCMS) is an automated system that processes and stores travelers’ information and track travel history in real...
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Gpu-based and streaming-enabled implementation of pre-processing flow towards enhancing optical character recognition accuracy and efficiency
Research has demonstrated that digital images can be pre-processed through operations such as scaling, rotation, and blurring to enhance the accuracy...
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A Deep Neural Network Based Holistic Approach for Optical Character Recognition of Handwritten Documents
Optical Character Recognition of handwritten document has been a research topic for last few decades now. Different type of classification schemes...
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Ensemble deep learning model for optical character recognition
In modern deep learning, character recognition in images is a very important field of study due to its has many real life applications. The goal of...
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Multimodal fine-grained grocery product recognition using image and OCR text
Automatic recognition of grocery products can be used to improve customer flow at checkouts and reduce labor costs and store losses. Product...
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CNN-based Thai handwritten OCR: an application for automated mail sorting
Automated mail sorting machines commonly use Optical Character Recognition (OCR) to recognize destination postcodes on envelopes and sort them...
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A multifaceted evaluation of representation of graphemes for practically effective Bangla OCR
Bangla Optical Character Recognition (OCR) poses a unique challenge due to the presence of hundreds of diverse conjunct characters formed by the...
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A hybrid convolutional neural network and support vector machine classifier for Amharic character recognition
Optical character recognition is a way of converting scanned images of printed or handwritten documents into machine-encoded text, making it easier...
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Sanskrit OCR System
The use of optical character recognition technology has become increasingly important for researchers in recognition techniques. Recognition of...
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Xamã : Optical character recognition for multi-domain model management
The development of systems following model-driven engineering can include models from different domains. For example, to develop a mechatronic...
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Testing and Improvement of OCR Recognition Technology in Export-Oriented Chinese Dictionary APP
With the increasing number of Chinese learners each year, the international influence of the Chinese language has also grown. Consequently, Chinese...
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Offline MODI script character recognition using deep learning techniques
Deep learning is a multilayer neural network learning algorithm which emerged in recent years. It has brought a new wave to machine learning and...
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Typewritten OCR Model for Ethiopic Characters
Optical Character Recognition (OCR) is the electronic conversion of images of computer-written, typewritten, handwritten, or printed text into...
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Evaluating and mitigating the impact of OCR errors on information retrieval
Optical character recognition (OCR) is typically used to extract the textual contents of scanned texts. The output of OCR can be noisy, especially...
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Tigrinya OCR: Applying CRNN for Text Recognition
Tigrinya is a language predominantly spoken in Eritrea and the Tigray region of Ethiopia. It is classified as a low resourced language when it comes...
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Few-Shot Learning for Character Recognition in Persian Historical Documents
Digitizing historical documents is crucial for the preservation of cultural heritage. The digitization of documents written in Perso-Arabic scripts,...