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Journal articles on the topic 'Tesseract.js'

Author: Grafiati

Published: 9 September 2021

Last updated: 29 July 2025

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1

M K, Akash. "Smart Education: An English Text-to- Indian Regional Language Translator." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47376.

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ABSTRACT Communication and learning are fundamental to education, but language barriers often hinder access to quality resources for non-English speakers in India. Smart Education is a modern web-based translation tool designed to convert educational content from English to Indian regional languages such as Hindi, Kannada, Tamil, and Telugu. With multilingual support, the tool leverages advanced technologies like Tesseract.js for image text extraction, Mammoth.js for DOCX files, PDF.js, and the MyMemory API for accurate translation. It supports various formats including text, Word documents, P

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2

Ketterer, David. "Tesseracts." Science Fiction Studies 22, Part 2 (1995): 299–301. https://doi.org/10.1525/sfs.22.2.0299a.

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3

Aravind, P. K. "The magic tesseracts and Bell’s theorem." American Journal of Physics 69, no. 3 (2001): 348–53. http://dx.doi.org/10.1119/1.1313518.

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4

Greene, Kenton, Christian Hansen, B. Barry Narod, Richard Dvorsky, and David M. Miles. "Tesseract – a high-stability, low-noise fluxgate sensor designed for constellation applications." Geoscientific Instrumentation, Methods and Data Systems 11, no. 2 (2022): 307–21. http://dx.doi.org/10.5194/gi-11-307-2022.

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Abstract. Accurate high-precision magnetic field measurements are a significant challenge for many applications, including constellation missions studying space plasmas. Instrument stability and orthogonality are essential to enable meaningful comparison between disparate satellites in a constellation without extensive cross-calibration efforts. Here we describe the design and characterization of Tesseract – a fluxgate magnetometer sensor designed for low-noise, high-stability constellation applications. Tesseract's design takes advantage of recent developments in the manufacturing of custom l

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5

Sims, Christopher. "Formation of Tesseract Time Crystals on a Quantum Computer." Crystals 13, no. 8 (2023): 1265. http://dx.doi.org/10.3390/cryst13081265.

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The engineering of new states of matter through Floquet driving has revolutionized the field of condensed matter physics. This technique enables the creation of hybrid topological states and ordered phases that are absent in normal systems. Crystalline structures, exemplifying spatially ordered systems under periodic driving, have been extensively studied. However, recent focus has shifted towards discrete time crystals (DTCs), periodically driven quantum many-body systems that break time translation symmetry under specific conditions. In this paper, the model of discrete time crystals is exte

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Baruah, Priyankush Kaushik, and Dr Pranabjyoti Haloi. "Development and Implementation of a Custom License Plate Detection and Recognition System Using YOLOv10 and Tesseract OCR: A Comprehensive Study in Computer Vision and Optical Character Recognition Technologies." International Journal of Innovative Technology and Exploring Engineering 14, no. 6 (2025): 20–26. https://doi.org/10.35940/ijitee.e1083.14060525.

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This study presents an automated license plate detection and recognition system, combining YOLOv10 for Realtime object detection and Tesseract OCR for robust text extraction. The methodology involves training a customised YOLOv10 model on annotated vehicle datasets to localize license plates, followed by region-of-interest (ROI) filtering to enhance accuracy. Detected plates are processed with Tesseract OCR to convert visual data into machine-readable text. Evaluated using precision, recall, and inference speed metrics, the system achieves 97 Parsant detection accuracy and real-time performanc

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Balasubramanian, Krishnan. "Recursive Symmetries: Chemically Induced Combinatorics of Colorings of Hyperplanes of an 8-Cube for All Irreducible Representations." Symmetry 15, no. 5 (2023): 1031. http://dx.doi.org/10.3390/sym15051031.

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We outline symmetry-based combinatorial and computational techniques to enumerate the colorings of all the hyperplanes (q = 1–8) of the 8-dimensional hypercube (8-cube) and for all 185 irreducible representations (IRs) of the 8-dimensional hyperoctahedral group, which contains 10,321,920 symmetry operations. The combinatorial techniques invoke the Möbius inversion method in conjunction with the generalized character cycle indices for all 185 IRs to obtain the generating functions for the colorings of eight kinds of hyperplanes of the 8-cube, such as vertices, edges, faces, cells, tesseracts, a

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Chesley, Emily, Jillian Marcantonio, and Abigail Pearson. "Towards Syriac Digital Corpora: Evaluation of Tesseract 4.0 for Syriac OCR." Hugoye: Journal of Syriac Studies 22, no. 1 (2019): 109–92. http://dx.doi.org/10.31826/hug-2019-220105.

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Abstract This paper summarizes the results of an extensive test of Tesseract 4.0, an open-source Optical Character Recognition (OCR) engine with Syriac capabilities, and ascertains the current state of Syriac OCR technology. Three popular print types (S14, W64, and E22) representing the Syriac type styles Estrangela, Serto, and East Syriac were OCRed using Tesseract’s two different OCR modes (Syriac Language and Syriac Script). Handwritten manuscripts were also preliminarily tested for OCR. The tests confirm that Tesseract 4.0 may be relied upon for printed Estrangela texts but should be used

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Benaissa, Ali, Abdelkhalak Bahri, Ahmad El Allaoui, and My Abdelouahab Salahddine. "Build a Trained Data of Tesseract OCR engine for Tifinagh Script Recognition." Data and Metadata 2 (December 9, 2023): 185. http://dx.doi.org/10.56294/dm2023185.

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This article introduces a methodology for constructing a trained dataset to facilitate Tifinagh script recognition using the Tesseract OCR engine. The Tifinagh script, widely used in North Africa, poses a challenge due to the lack of built-in recognition capabilities in Tesseract. To overcome this limitation, our approach focuses on image generation, box generation, manual editing, charset extraction, and dataset compilation. By leveraging Python scripting, specialized software tools, and Tesseract's training utilities, we systematically create a comprehensive dataset for Tifinagh script recog

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10

Padmaja, G., Swetha Pesaru, Desidi Narsimha Reddy, D. Anitha Kumari, and Shiva Prasad Maram. "Robust Vehicle Number Plate Text Recognition and Data Analysis Using Tesseract Ocr." ITM Web of Conferences 74 (2025): 01009. https://doi.org/10.1051/itmconf/20257401009.

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To detect the vehicle number plate the system should understand the character and integers determined on vehicles. The proposed methodology holds three phases: pre-process, extraction of features and recognition of text. These phases include some operations like grey scale, adaptive threshold, morphological for extraction of characters and numbers from different quality of the images in pre-processing stage. By transforming the images to grey scale, this can remove the extraneous colours and extracts the appropriate values. In morphological removes the borders and removes the background noises

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Rawat, Sukhbindra Singh, Ashutosh Sharma, and Rachana Gusain. "ANALYSIS OF IMAGE PREPROCESSING TECHNIQUES TO IMPROVE OCR OF GARHWALI TEXT OBTAINED USING THE HINDI TESSERACT MODEL." ICTACT Journal on Image and Video Processing 12, no. 2 (2021): 2588–94. http://dx.doi.org/10.21917/ijivp.2021.0366.

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A huge amount of information exists in the form of textbooks, paper documents, newspapers, and other physical forms, that is required to be digitized for its effective access and long-time availability. Optical Character Recognition (OCR) is an effective way to digitize the text. In this study, we have used Google’s Tesseract as the OCR tool. The focus of our study is to improve Tesseract’s accuracy on machine-printed Garhwali documents by using image pre-processing techniques including Super-Resolution (SR), different binarization methods (Otsu and adaptive thresholding), skew correction, mor

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12

Tiwari, Anurag. "Data Extraction from Images through OCR." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (2021): 435–37. http://dx.doi.org/10.22214/ijraset.2021.37377.

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The paperwork used in maintaining various types of documents in our daily lives is tiresome and inefficient, it consumes a lot of time and it is difficult to maintain and remember the concerned documents. This project provides a solution to these problems by introducing Optical Character Recognition Technology (OCR) which runs on Tesseract OCR Engine. The project specifically aims at increasing data accessibility, usability and improving customer experience by decreasing the time spent to process, save, and maintain user data. Another objective of this project is to nullify the human error, wh

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13

Greene, Kenton, Scott R. Bounds, Robert M. Broadfoot, et al. "First in situ measurements of the prototype Tesseract fluxgate magnetometer on the ACES-II-Low sounding rocket." Geoscientific Instrumentation, Methods and Data Systems 13, no. 2 (2024): 249–62. http://dx.doi.org/10.5194/gi-13-249-2024.

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Abstract. Ongoing innovation in next-generation fluxgate magnetometry is important for enabling future investigations of space plasma, especially multi-spacecraft experimental studies of energy transport in the magnetosphere and the solar wind. Demonstrating the spaceflight capability of novel designs is an important step in the instrument development process; however, large-scale satellite missions are often unwilling to accept the risks of an instrument without flight heritage. The Tesseract – a novel fluxgate magnetometer sensor design – had an opportunity for an inaugural spaceflight demon

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14

Patience, Okechukwu Ogochukwu, Eziechina Malachy Amaechi, Onyemachi George, and Onuwa Nnachi Isaac. "Enhanced Text Recognition in Images Using Tesseract OCR within the Laravel Framework." Asian Journal of Research in Computer Science 17, no. 9 (2024): 58–69. http://dx.doi.org/10.9734/ajrcos/2024/v17i9499.

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This research explores the integration of Tesseract OCR (Optical Character Recognition) within the Laravel framework to enhance text recognition capabilities in images. Tesseract OCR, an open-source OCR engine, is renowned for its accuracy and efficiency in converting various image formats into editable and searchable text. However, leveraging its full potential within a robust web application framework presents unique challenges and opportunities. This implementation focuses on creating a seamless, user-friendly application that processes images uploaded by users and accurately extracts text

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15

Chen, Sheng, Jiankang Zhao, Hongyang Su, et al. "Pd–Pt Tesseracts for the Oxygen Reduction Reaction." Journal of the American Chemical Society, January 1, 2021. http://dx.doi.org/10.1021/jacs.0c12282.

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16

Besada, José L., Corentin Guichaoua, and Moreno Andreatta. "From Dürer's Magic Square to Klumpenhouwer Tesseracts: On Melencolia (2013) by Philippe Manoury." Music Analysis, May 13, 2022. http://dx.doi.org/10.1111/musa.12176.

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