Relevant bibliographies by topics / OCR

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'OCR'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 March 2025

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Journal articles on the topic "OCR"

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Amin, Hawraz Ibrahim M., Kamaran Abdoulrahman, Azad S. Sadraddin, Heman A. Smail, Zanko Hassan Jawhar, Kovan Dilawer Issa, Chabaco Armijos, and Giovanni Vidari. "Chemical Composition and In Vitro Evaluation of Antioxidant and Antiproliferative Effects of Volatile Oils Hydrodistilled from Onobrychis carduchorum C.C. Towns., a Kurdish Traditional Plant." Plants 12, no. 16 (August 21, 2023): 3013. http://dx.doi.org/10.3390/plants12163013.

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The volatile oils hydrodistilled from the aerial parts and roots of O. carduchorum C.C Towns. (Fabaceae) have been chemically characterized for the first time. A total of 43 constituents with an abundance >0.03% were identified and quantified in the two oils by GC/MS and GC/FID analyses. They comprise 38 components (98.58%) of the oil isolated from the aerial parts (OCA) and 34 components (93.33%) of the oil from the roots (OCR). Six constituents, α-pinene (23.11 ± 0.1%), β-elemene (17.33 ± 0.1%), 1,8-cineole (12.15 ± 0.2%), furfural (7.91 ± 0.1%), terpineol-4-ol (6.32 ± 0.2%), and limonene (4.13 ± 0.1%), accounted for about 75% of the total OCA oil. On the other hand, 1,8-cineole (15.79 ± 0.1%), furfural (10.44 ± 0.1%), β-elemene (10.14 ± 0.2%), α-terpineol (7.74 ± 0.1%), linalool (7.45 ± 0.1%), and α-pinene (4.76 ± 0.1%) made up about 60% of the OCR oil. The IC50 values of the scavenging activities of the OCA and OCR oils towards the DPPH radical and H2O2 were 79.8 ± 0.5 and 153.3 ± 0.6 μg/mL and 394.09 ± 0.2 and 311.67 ± 0.4 μg/mL, respectively. In addition, in the MTS assay, the OCA and OCR oils showed significant antiproliferative effects against T47D, MDA-MB-453, BG-1, and A549 human cancer cells that were more powerful than those against two normal human cell lines, HEK-293 and HFF-1. The abundant presence of β-elemene as an antiproliferative component of the two oils suggested the existence of a new chemotype of O. carduchorum.
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Jing, Qi, Yonghui Xie, and Di Zhang. "Effects of Channel Outlet Configuration and Dimple/Protrusion Arrangement on the Blade Trailing Edge Cooling Performance." Applied Sciences 9, no. 14 (July 19, 2019): 2900. http://dx.doi.org/10.3390/app9142900.

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The trailing edge regions of high-temperature gas turbine blades are subjected to extremely high thermal loads and are affected by the external wake flow during operation, thus creating great challenges in internal cooling design. With the development of cooling technology, the dimple and protrusion have attracted wide attention for its excellent performance in heat transfer enhancement and flow resistance reduction. Based on the typical internal cooling structure of the turbine blade trailing edge, trapezoidal cooling channels with lateral extraction slots are modeled in this paper. Five channel outlet configurations, i.e., no second passage (OC1), radially inward flow second passage (OC2), radially outward flow second passage (OC3), top region outflow (OC4), both sides extractions (OC5), and three dimple/protrusion arrangements (all dimple, all protrusion, dimple–protrusion staggered arrangement) are considered. Numerical investigations are carried out, within the Re range of 10,000–100,000, to analyze the flow structures, heat transfer distributions, average heat transfer and friction characteristics and overall thermal performances in detail. The results show that the OC4 and OC5 cases have high heat transfer levels in general, while the heat transfer deterioration occurs in the OC1, OC2, and OC3 cases. For different dimple/protrusion arrangements, the protrusion case produces the best overall thermal performance. In conclusion, for the design of trailing edge cooling structures with lateral slots, the outlet configurations of top region outflow and both sides extractions, and the all protrusion arrangement, are recommended.
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Andrianakis, A., P. Kiss, U. Moser, A. Wolf, C. Holzmeister, A. Koutp, P. Grechenig, U. Pilsl, and P. V. Tomazic. "Extent of optico-carotid recess is significantly associated with presence of bony dehiscences and bone thickness in the optico-carotid area." Rhinology Online 4, no. 4 (February 4, 2021): 85–90. http://dx.doi.org/10.4193/rhinol/21.014.

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Background: The objectives of this study were to evaluate the frequency of bony dehiscences in the optico-carotid recess (OCR) area and to measure the thickness of the bony lamellas bordering the OCR, according to our previously proposed OCR classification taking into account the extent of the recess. Methodology: A total of 100 human cadaver heads (n= 200 sphenoid sinuses) were investigated. Samples were divided into groups according to the presence and extent of OCR (no OCR, sub-optical OCR, latero-optical OCR). Bony dehiscences were visually identified and bone thickness was measured by using a high-resolution micrometer. Results: A bony dehiscence in the OCR area was observed in 20%. A significant difference in bony dehiscence occurrence rate between OCR types was found. The wall thickness of the bony carotid artery- and optic nerve canals bordering the OCR were 0.25 ± 0.16 mm and 0.27 ± 0.15 mm, respectively. Significant differences between OCR groups in bony wall thickness of the carotid artery canal and optic nerve canal were found. Samples with a latero-optical OCR had a significant thinner wall of the carotid artery and optic nerve canal than samples with a sub-optical OCR and no OCR. Conclusions: The current results indicate that the presence of an extended OCR, e.g. latero-optical, is highly associated with a greater risk of bony dehiscences and thinner bony lamellas in the OCR region.
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Prasetijo, Hari, Ari Fadli, and Feby Renaldi. "Improved Over Current Relay (OCR) Coordination Using Time Multiple Setting (TMS)." MATEC Web of Conferences 402 (2024): 02001. http://dx.doi.org/10.1051/matecconf/202440202001.

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Proper coordination between overcurrent relay (OCR) is needed to improve the reliability of the power distribution system. By choosing the proper time multiple setting (TMS), an optimum setting of OCR coordination can be achieved. This study improve working time coordination of OCR bay transformer using time multiple setting. Simulations were carried out to see the performance of the OCR bay transformer against a 3 phase short circuit on the 20 kV outgoing bus. The 3 phase short circuit was chosen because it produces the largest fault current among other types of short circuits. The discussion focuses on the OCR bay transformer, consist of OCR incoming 20 kV and OCR outgoing 150 kV. Existing data and calculation results were used as a parameter in the simulation. Simulation results with existing tms 0.21 and 0.23 for OCR incoming 20 kV and OCR outgoing 150 kV, respectively, have the potential to cause miscoordination of the OCR working time. Smaller short circuit current, bigger potential miscoordination. Resetting tms improves coordination of OCR bay transformer working time according to the standard used. Bigger value of tms, as long as it meets the standar, better OCR working time coordination to protect phase-phase fault current.
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van Aardt, Willie J., Hendrika Fourie, Marthinus Pretorius, Roan Louw, and Hayley van Dyk. "The effects of stirring, population levels and a potential anti-nematodal product on the respiration of second-stage juveniles of Meloidogyne incognita measured with different technology." Nematology 18, no. 9 (2016): 1053–61. http://dx.doi.org/10.1163/15685411-00003014.

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The oxygen consumption rate (OCR) ofMeloidogyne incognitasecond-stage juveniles (J2) was measured using polarographic oxygen sensor (POS) and fibre-optic oxygen sensor (FOS) technology. The effect of stirring speed on the OCR of J2 suspended in tap water was determined using POS. Next, the OCR of different J2 numbers was measured using FOS. Also, the OCR of J2 in tap water using POS and FOS was recorded, and also the effect of SoilBioMuti (SBM) on J2 OCR using FOS. Stirring speed had no pronounced effect on the OCR of J2. FOS recorded the OCR of as few as five J2. The OCR of J2 in sterile tap water was significantly lower for POS than FOS. Using FOS, non-filtered (NF) SBM without J2 had the highest OCR, being 42% higher than that of NF SBM with J2. The two filtered SBM (with and without J2) treatments had the lowest OCR values.
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Dannélls, Dana, and Simon Persson. "Supervised OCR Post-Correction of Historical Swedish Texts." Digital Humanities in the Nordic and Baltic Countries Publications 3, no. 1 (June 1, 2020): 24–37. http://dx.doi.org/10.5617/dhnbpub.11176.

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Current approaches for post-correction of OCR errors offer solutions that are tailored to a specific OCR system. This can be problematic if the postcorrection method was trained on a specific OCR system but have to be applied on the result of another system. Whereas OCR post-correction of historical text has received much attention lately, the question of what role does the OCR system play for the post-correction method has not been addressed. In this study we explore a dataset of 400 documents of historical Swedish text which has been OCR processed by three state-of-the-art OCR systems: Abbyy Finereader, Tesseract and Ocropus. We examine the OCR results of each system and present a supervised machine learning post-correction method that tries to approach the challenges exhibited by each system. We study the performance of our method by using three evaluation tools: PrimA, Sprakbanken evaluation tool and Frontiers Toolkit. Based on the evaluation analysis we discuss the impact each of the OCR systems has on the results of the post-correction method. We report on quantitative and qualitative results showing varying degrees of OCR postprocessing complexity that are important to consider when developing an OCR post-correction method.
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Mast, Fred W. "Does the world rock when the eyes roll?" Swiss Journal of Psychology 59, no. 2 (June 2000): 89–101. http://dx.doi.org/10.1024//1421-0185.59.2.89.

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When the head is inclined sideways, the eyes are counter-rotated with respect to the head (ocular-counterroll, OCR). In man, the gain of OCR in static body tilts is limited to about 10% of the angle of roll tilt, which suggests that its function is vestigial. However, it is still unclear how the residual OCR is related to the perceived orientation of visual stimuli. Wade and Curthoys (1997) claim that the brain does not “take into account” the OCR, so that the eye position directly interferes with perception of visual orientation. Alternately, it has been argued that OCR is partly compensated by an extraretinal eye-position information such as, e.g., an efference copy ( Haustein, 1992 ; Haustein & Mittelstaedt, 1990 ). The two experiments reported in this study are targeted towards critically examining this inter-relation between OCR and perceived visual orientation. The latter was assessed via the subjective visual vertical, SVV, which is determined when a subject judges the orientation of an indicator (e.g., a short line segment) as apparently vertical. The OCR was measured by using a video-oculographic system. In Experiment 1, a human centrifuge was used to test the effect of an increase of the gravito-inertial force (GIF) on SVV and OCR. Experiment 2 was inspired by the fact that OCR can also be elicited during “barbecue rotation”. Again, it was the aim to compare OCR and SVV in different body positions, such as pure roll and barbecue rotated tilts. The present study provides convincing experimental evidence that SVV is widely uninfluenced by the course of OCR. Increasing the GIF in Experiment 1 had a divergent effect on SVV and OCR; the gain of OCR increases whereas the SVV changed differently, at obtuse tilt angles even in the opposite direction. OCR and SVV were again found to dissociate in Experiment 2, which emphasizes the fact that the SVV and OCR are not controlled by the same neural mechanism, but rather use different spatial reference information.
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Muthusundari, Muthusundari, A. Velpoorani, S. Venkata Kusuma, Trisha L, and Om k. Rohini. "Optical character recognition system using artificial intelligence." LatIA 2 (August 13, 2024): 98. http://dx.doi.org/10.62486/latia202498.

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Abstract A technique termed optical character recognition, or OCR, is used to extract text from images. An OCR the system's primary goal is to transform already present paper-based paperwork or picture data into usable papers. Character as well as word detection are the two main phases of an OCR, which is designed using many algorithms. An OCR also maintains a document's structure by focusing on sentence identification, which is a more sophisticated approach. Research has demonstrated that despite the efforts of numerous scholars, no error-free Bengali OCR has been produced. This issue is addressed by developing an OCR for the Bengali language using the latest 3.03 version of the Tesseract OCR engine for Windows.
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Tezer, Damla Çetinkaya, Ipek Gungor Dogan, Melek Colak Atmaca, Murat Mert Atmaca, and Serkan Demir. "Does pandemic change the ocrelizumab therapy approach? Yes. : Single center ocrelizumab experience." Ideggyógyászati szemle 75, no. 11-12 (2022): 411–17. http://dx.doi.org/10.18071/isz.75.0411.

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We know that treatment algorithms have changed in Multiple Sclerosis (MS) practice during the pandemic. In this study, we aimed to investigate whether there was a change in the patient population for ocrelizumab (OCR) treatment during the pandemic period, the treatment compliance of the patients, and the course of the Coronavirus Disease-19 (COVID-19) disease in the patients who received OCR. Our study was designed as a survey study. A questionnaire was sent to the patients assessing whether they had COVID-19 infection, whether they received treatments regularly before and after the pandemic, vaccination status and duration of OCR treatment. Demographic characteristics of the patients, treatments they used before, MS type, Expanded Disability Status Scale (EDSS) scores were determined from the database. Each group of OCR started before pandemic and OCR started after pandemic were compared. We included into the study 86 patients who started OCR before pandemic period and 75 patients who started OCR after the pandemic. Demographic features were similar. EDSS scores were higher in the group that started OCR treatment before the pandemic (p<0.0001). The patients who started OCR treatment before the pandemic had more disruptions than which started during the pandemic (p<0.0001). No correlation was found between the duration of OCR treatment and COVID-19 infection (p=0.940). We observed that the patients who had severe COVID-19 infection had received OCR therapy for a longer period. This retrospective study concluded that the OCR treatment approach in our center had changed during the pandemic period. OCR therapy was started in patients with less disability. The possible reasons for this situation include the proven relationship between high EDSS and serious COVID-19 infection, and that the patients who have higher EDSS score had troubles in reaching health institutions during the pandemic. The result that patients with severe COVID-19 infection received OCR treatment for a longer period necessitates more evidence-based research to investigate the relationship between treatment duration and disease severity.
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Sisodia, Prakhar. "Optical Character Recognition Development Using Python." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 4, no. 3 (2023): 1–13. http://dx.doi.org/10.54060/jieee.2023.75.

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Optical Character Recognition (OCR) is a technology used to convert scanned or digital images into editable text. OCR has become an increasingly important tool in the fields of data extraction and information retrieval, allowing for quick and efficient conversion of scanned documents and digital images into text. In this paper, we explore the use of the Python programming language to implement OCR algorithms and systems. We provide a comprehensive overview of existing Python libraries and packages used for OCR, including Tesseract and pytesseract, along with their strengths and limitations. We also examine the different OCR approaches and techniques, including template matching, feature extraction, and encrypting/decrypting the OCR parsed files and discuss their implementation in Python. Finally, we present a case study of a simple OCR system built using Python and evaluate its performance on a sample dataset. The results of our study highlight the potential of Python for OCR implementation and demonstrate its feasibility for real-world applications.
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Dissertations / Theses on the topic "OCR"

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McDonald, Mercedes Terre. "OCR: A STATISTICAL MODEL OF MULTI-ENGINE OCR SYSTEMS." Master's thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4459.

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This thesis is a benchmark performed on three commercial Optical Character Recognition (OCR) engines. The purpose of this benchmark is to characterize the performance of the OCR engines with emphasis on the correlation of errors between each engine. The benchmarks are performed for the evaluation of the effect of a multi-OCR system employing a voting scheme to increase overall recognition accuracy. This is desirable since currently OCR systems are still unable to recognize characters with 100% accuracy. The existing error rates of OCR engines pose a major problem for applications where a single error can possibly effect significant outcomes, such as in legal applications. The results obtained from this benchmark are the primary determining factor in the decision of implementing a voting scheme. The experiment performed displayed a very high accuracy rate for each of these commercial OCR engines. The average accuracy rate found for each engine was near 99.5% based on a less than 6,000 word document. While these error rates are very low, the goal is 100% accuracy in legal applications. Based on the work in this thesis, it has been determined that a simple voting scheme will help to improve the accuracy rate.
M.S.
Department of Electrical and Computer Engineering
Engineering and Computer Science
Electrical and Computer Engineering
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Peluch, Tibor. "OCR cíleně znehodnocených textů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218134.

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The thesis deals with programming of application in operating system Windows. Main features of application system Microsoft Foundation Class are resumed in brief here. In following part there is idea about implementing an application with graphic user interface that makes, using schema, work with data, possible. The third part deals with implementation of blocks into dynamic linked libraries and there is outlined a possibility to use data of this programme as an external module and a possibility of realtime data processing e.g. picture and sound. The verification of a good functionality of this application is in the last part. The application is really tested in diagnosing of devaluated texts for protecting web forms www.centrum.cz. There were designed blocks making picture read possible just from internet, preprocessing, segmentation, feature extraction, evaluationg in neural network and blocks that make possible to read and save processed data into the disc.
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Belgiovine, Mauro. "Advanced industrial OCR using Autoencoders." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13807/.

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Il contenuto di questa tesi di laurea descrive il lavoro svolto durante un tirocinio di sei mesi presso Datalogic ADC. L'obiettivo del lavoro è stato quello di utilizzare uno specifico tipo di rete neurale, chiamata Autoencoder, per scopi legati al riconoscimento o alla convalida di caratteri in un sistema OCR industriale. In primo luogo è stato creato un classificatore di immagini di caratteri basato su Denoising Autoencoder; successivamente, è stato studiato un metodo per utilizzare l'Autoencoder come un classificatore di secondo livello, per meglio distinguere le false attivazioni da quelle corrette in condizioni di incertezza di un classificatore generico. Entrambe le architetture sono state valutate su dataset reali di clienti di Datalogic e i risultati sperimentali ottenuti sono presentati in questa tesi.
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Noghe, Petr. "Vyhodnocení testových formulářů pomocí OCR." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-219986.

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This thesis deals with the evaluation forms using optical character recognition. Image processing and methods used for OCR is described in the first part of thesis. In the practical part is created database of sample characters. The chosen method is based on correlation between patterns and recognized characters. The program is designed in a graphical environment MATLAB. Finally, several forms are evaluated and success rate of the proposed program is detected.
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Sahiti, Ylli. "OCR algoritmers noggrannhet och snabbhet vid identifieringen av text på olika typer av bakgrund : En jämförelse mellan OCR - algoritmerna Tesseract och Google ML-Kit." Thesis, Jönköping University, JTH, Avdelningen för datateknik och informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53789.

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SyfteOCR, optical character recognition, algoritmer kan implementeras på olika sätt, de påverkar även resultatet både beroende på vilken implementation som används och vilket dataset som det används på. Därför är det viktigt att testa de olika OCR algoritmerna på just det dataset som är tänkt att användas för att få ett förutsägbart resultat. Metod60 bilder är tagna på innehållsförteckningar tryckta på svenska livsmedelsprodukter med tre olika bakgrundsytor, aluminium, konvexa ytor och mjukplast. Två OCR algoritmer, ML Kit och Tesseract, har jämförts med avseende på precision och hastighet i syfte att hitta svårigheter för de respektive algoritmerna. ResultatBåda undersökta OCR algoritmerna hade störst svårighet att identifiera tecken i bilder med reflektion. ML Kit hade färre problem med lågupplösta bilder, Tesseract hade anmärkningsvärt större problem med lågupplösta bilder. För ändamålet som studien avser så är ML Kit det bästa valet. BegränsningarEnbart två OCR algoritmer jämförs i studien. Livsmedelsprodukter med tre olika bakgrundsytor har studerats, aluminium, konvex yta och mjukplast. Endast precision samt hastighet har jämförts. Precisionen har jämförts i antalet rätt ord samt hur nära en prediktering är från att vara helt rätt (Levenshtein algoritm).
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Dordevic, Larisa, and Ahlén Hanna Richter. "Motivation till och Upplevelsen av Hinderbanelopp : Obstacle Course Race (OCR)." Thesis, Högskolan i Halmstad, Akademin för hälsa och välfärd, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33625.

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Föreliggande studie syftade till att använda självbestämmandeteorin för att öka kunskapen om motiv till OCR-deltagande i Sverige genom att studera a) deltagarnas upplevelse av självbestämmande utifrån motivationsregleringarna, b) om de grundläggande psykologiska behoven tillfredsställs i deltagandet och c) vilka egenskaper (t.ex. utformning av loppen, svårighetsgrad på hinder, omgivning) i själva OCR-eventet som kan relateras till dessa faktorer. OCR räknas som en av de snabbast växande sporterna i världen och verkar utmana samt attrahera en stor mångfald. En kvalitativ forskningsmetod användes där åtta deltagare (3 kvinnor och 5 män) från sydvästra Sverige intervjuades för att få en djupgående inblick i motivationen samt upplevelsen av eventen. Samtliga deltagare hade deltagit i minst ett OCRevent i Sverige innan intervjuerna. Intervjuerna samt analyserna var baserade på de tre grundläggande psykologiska behoven och motivationsregleringarna utifrån Självbestämmandeteorin (SDT). Studiens huvudsakliga fynd indikerade att deltagande i OCR bidrog till både inre och yttre motivation och att samtliga behov utifrån SDT tillfredsställdes, vilket genererade i att en hög nivå av självbestämmande upplevdes bland deltagarna. Vidare visade resultaten att det fanns motivationsfaktorer, exempelvis den sociala omgivningen, glädjen, utmaningen och utvecklingen, som hade större påverkan än andra faktorer. Det ansågs i den föreliggande studien att deltagarna upplevde en hög nivå av självbestämmande och att OCR kan bidra till ett ökat psykologiskt välbefinnande. Framtida forskning bör studera ett större och mer slumpmässigt urval för att öka generaliserbarheten men även ta del av de negativa hälsoeffekterna OCR (extremsport) skulle kunna bidra till.
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Lund, Mikael. "Hur ser framtiden ut för OCR?" Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20561.

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Examensarbetet handlar om OCR (Optical Character Recognition). OCR-tekniken går utpå att konvertera inskannade bilder från maskinskriven eller handskriven text (siffror, bokstäver och symboler) till datorformat.Syftet med detta examensarbete är att utforska OCRs framtid och vilka användningsområden som finns idag för tekniken. Det intressanta är att se hur OCR klarar sig när mer och mer material är digitala.Genomförandet till detta examensarbete har gjorts med information från böcker, Internet,mejl och genom att tittat närmare på ett företag inom den grafiska branschen som använder sig av OCR, nämligen Aftonbladet. Jag har även testat ett OCR-program, ABBYYsFineReader 8 och gjort tester med några testteman, exempelvis matematiktest och olikatester på artiklar från några tidningar.Mina slutsatser är att OCR har en framtid men tekniken har en del förbättringsmöjligheter,exempelvis tolkning av handskrivna texter. OCR kan finnas kvar även när mer och mermaterial blir digitala om det integreras i befintliga tekniker, som i ett spam-filter för att tolka texten i bilden. Den nuvarande OCR-tekniken fungerar bra om materialet ärmaskinskrivet och i bra skick men den måste bli bättre på att tolka handskrivna texter för att kunna användas vid arkiveringsbehov av sådana texter.
My examination subject is about OCR (Optical Character Recognition). The idea of OCRtechnology is to convert scanned images of machine-printed or handwritten text (numerals, letters and symbols) into a computer-processable format.The purpose of my examination subject is to explore the future of OCR and why to use it today. It’s interesting to see if OCR survives when more and more material is digital.The implementations to the examination subject have been made from books, Internet, e-mail and I have discovered how a company in the graphic industry are using OCR, namely Aftonbladet.I have also tested an OCR-program, ABBYYs FineReader 8, and done some testing with some testthemes, for example mathematics test and different tests on articles from a few magazines.My conclusions are that OCR has a future but the technology needs some improvements, forexample interpreting handwritten texts. OCR can exist, even when more and more material is digital, if its integrated with existing technologies, for example with a spam-filter to interpret the text within in the picture. The current OCR-technology works fine with machine-printed material, and when the document quality is good. However it needs to be on handwritten text to be used forarchiving needs.
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Serafini, Sara. "Machine Learning applied to OCR tasks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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The content of this thesis describes the work done during a six-month internship at Datalogic, in its research laboratories in Pasadena (CA). The aim of my research was to implement and evaluate a classifier as part of an industrial OCR system for learning purposes and to see how well it could work in comparison to current best Datalogic products, since it might be simpler/faster, it might be a good alternative for implementing on an embedded system (where current Datalogic products may not be able to run fast enough).
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Nilsson, Elin. "Test av OCR-verktyg för Linux." Thesis, Linnaeus University, School of Computer Science, Physics and Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-5906.

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Denna rapport handlar om att ta fram ett OCR-verktyg för digitalisering av pappersdokument. Krav på detta verktyg är att bland annat det ska vara kompatibelt med Linux, det ska kunna ta kommandon via kommandoprompt och dessutom ska det kunna hantera skandinaviska tecken.

Tolv OCR-verktyg granskades, sedan valdes tre verktyg ut; Ocrad, Tesseract och OCR Shop XTR. För att testa dessa scannades två dokument in och digitaliserades i varje verktyg.

Resultatet av testerna är att Tesseract är de verktyget som är mest precist och Ocrad är det verktyget som är snabbast. OCR Shop XTR visar på sämst resultat både i tidtagning och i antal korrekta ord.


This report is about finding OCR software for digitizing paper documents. Requirements were to include those which were compatible with Linux, being able to run commands via the command line and also being able to handle the Scandinavian characters.

Twelve OCR softwares were reviewed, and three softwares were chosen; Ocrad, Tesseract and OCR Shop XTR. To test these, two document were scanned and digitized in each tool.

The results of the tests are that Tesseract is the tool which is the most precise and Ocrad is the tool which is the fastest. OCR Shop XTR shows the worst results both in timing and number of correct words.

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Buchal, Petr. "Využití neanotovaných dat pro trénování OCR." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445580.

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The creation of a high-quality optical character recognition system (OCR) requires a large amount of labeled data. Obtaining, or in other words creating, such a quantity of labeled data is a costly process. This thesis focuses on several methods which efficiently use unlabeled data for the training of an OCR neural network. The proposed methods fall into the category of self-training algorithms. The general approach of all proposed methods can be summarized as follows. Firstly, the seed model is trained on a limited amount of labeled data. Then, the seed model in combination with the language model is used for producing pseudo-labels for unlabeled data. Machine-labeled data are then combined with the training data used for the creation of the seed model and they are used again for the creation of the target model. The successfulness of individual methods is measured on the handwritten ICFHR 2014 Bentham dataset. Experiments were conducted on two datasets which represented different degrees of labeled data availability. The best model trained on the smaller dataset achieved 3.70 CER [%], which is a relative improvement of 42 % in comparison with the seed model, and the best model trained on the bigger dataset achieved 1.90 CER [%], which is a relative improvement of 26 % in comparison with the seed model. This thesis shows that the proposed methods can be efficiently used to improve the OCR error rate by means of unlabeled data.
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Books on the topic "OCR"

1

Sochacki, Frank. OCR A2 biology. London: Hodder Education, 2013.

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Fosbery, Richard. OCR AS biology. London: Philip Allan, 2008.

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(Organisation), OCR, ed. OCR AS economics. Deddington: Philip Allan Updates, 2008.

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Burrows, Charlotte. AS-Level Biology for OCR: The Complete Course for OCR. Broughton In Furness: Coordination Group Publications, 2012.

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Emma, Elder, Ellingham Jane, McCurrie Rosie, Rogers Rachael, Simson Camilla, Thompson Hayley, and Tyler Megan, eds. A2-Level Biology for OCR: The Complete Course for OCR. Broughton In Furness: Coordination Group Publications, 2012.

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Thompson, Graham. OCR PE for A2. London: Hodder Arnold, 2009.

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Mary, Jones. Biology 2 for OCR. Cambridge: Cambridge University Press, 2009.

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Nesta, Wiggins-James, and James Rob, eds. OCR PE for AS. London: Hodder Arnold, 2008.

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Shephard, Colin, and Rosemary Rees. Ocr Medieval History (OCR Modular History). Hodder Arnold, 2006.

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Ocr Medicine Investigations (OCR Modular History). Hodder Murray, 2004.

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Book chapters on the topic "OCR"

1

Colhoun, O. "OCR." In Lexikon der Medizinischen Laboratoriumsdiagnostik, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-49054-9_2288-1.

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Colhoun, O. "OCR." In Springer Reference Medizin, 1776. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-48986-4_2288.

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Chatfield, Tom. "OCR." In 50 Schlüsselideen Digitale Kultur, 132–35. Heidelberg: Spektrum Akademischer Verlag, 2013. http://dx.doi.org/10.1007/978-3-8274-3064-9_34.

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Gooch, Jan W. "OCR Inks." In Encyclopedic Dictionary of Polymers, 497. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_8080.

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Da, Cheng, Peng Wang, and Cong Yao. "Levenshtein OCR." In Lecture Notes in Computer Science, 322–38. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19815-1_19.

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Madarász, Gábor, Noémi Ligeti-Nagy, András Holl, and Tamás Váradi. "OCR Cleaning of Scientific Texts with LLMs." In Lecture Notes in Computer Science, 49–58. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65794-8_4.

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AbstractCorrecting Optical Character Recognition (OCR) errors is a major challenge in preprocessing datasets consisting of legacy PDF files. In this study, we develop Large Language Models specially finetuned to correct OCR errors. We experimented with the mT5 model (both the mT5-small and mT5-large configurations), a Text-to-Text Transfer Transformer-based machine translation model, for the post-correction of texts with OCR errors. We compiled a parallel corpus consisting of text corrupted with OCR errors as well as corresponding clean data. Our findings suggest that the mT5 model can be successfully applied to OCR error correction with improving accuracy. The results affirm the mT5 model as an effective tool for OCR post-correction, with prospects for achieving greater efficiency in future research.
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Madake, Jyoti, Yuvraj Yedle, Vaibhav Shahabade, and Shripad Bhatlawande. "Sanskrit OCR System." In Communications in Computer and Information Science, 188–200. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45121-8_16.

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Biten, Ali Furkan, Rubèn Tito, Lluis Gomez, Ernest Valveny, and Dimosthenis Karatzas. "OCR-IDL: OCR Annotations for Industry Document Library Dataset." In Lecture Notes in Computer Science, 241–52. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25069-9_16.

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Amin, Adnan. "Ocr of Arabic texts." In Lecture Notes in Computer Science, 616–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-19036-8_62.

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Wang, Chenyang, Yanhong Xie, Kai Wang, and Tao Li. "OCR with Adaptive Dictionary." In Lecture Notes in Computer Science, 611–20. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21963-9_56.

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Conference papers on the topic "OCR"

1

Sadeghian, Rasoul, Shahrooz Shahin, and Sina Sareh. "CVOCR: Context Vision OCR." In 2024 20th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), 1–7. IEEE, 2024. http://dx.doi.org/10.1109/mesa61532.2024.10704827.

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Salah, Ahmed Ben, Jean philippe Moreux, Nicolas Ragot, and Thierry Paquet. "OCR performance prediction using cross-OCR alignment." In 2015 13th International Conference on Document Analysis and Recognition (ICDAR). IEEE, 2015. http://dx.doi.org/10.1109/icdar.2015.7333823.

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Neudecker, Clemens, Konstantin Baierer, Maria Federbusch, Matthias Boenig, Kay-Michael Würzner, Volker Hartmann, and Elisa Herrmann. "OCR-D." In DATeCH2019: 3rd International Conference on Digital Access to Textual Cultural Heritage. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3322905.3322917.

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Ghosh, Subhankar, P. K. Bora, Sanjib Das, and B. B. Chaudhuri. "Development of an Assamese OCR using Bangla OCR." In Proceeding of the workshop. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2432553.2432566.

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Miura, Ken, Koji Kikuhara, Kazuki Tsukamoto, Ayush Kumar, and Akemi Ito. "A Study on Factors Affecting Oil Film Thickness on Sliding Surface of Three-Piece Oil Control Ring." In ASME 2024 ICE Forward Conference. American Society of Mechanical Engineers, 2024. https://doi.org/10.1115/icef2024-140870.

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Abstract Oil consumption of an engine causes particulate matter generation, catalyst poisoning in an aftertreatment device, and abnormal combustion such as pre-ignition. Oil control rings (OCRs) play a role of controlling amount of oil on the sliding surface and are important engine components in reducing oil consumption. Since the OCR has the highest ring tensions in the piston ring pack, the OCR is expected to fit into the cylinder bore. However, measurement data of the oil film thickness on the sliding surface of the OCR has shown that the actual oil film was thicker than the theoretical value. In this study, factors which affect the oil film thickness on the sliding surface of a three-piece oil control ring (TPOCR) were investigated by the direct measurement of the oil film thickness on the sliding surface and the lower flank of the TPOCR. Piston secondary motion in the actual engine was also measured to analyze the effect of lateral and tilting motion of the piston on the oil film thickness. Those effects were also analyzed using a rig tester. Posture of the OCR rails were also considered to analyze oil film thickness data. It was found that the lateral and the tilting motion of the piston affects the oil film thickness. It was shown that a certain posture of the OCR rail restrained expander movement and also caused a thicker oil film. The bore distortion in the circumferential direction was one of factors. Those findings suggest that piston, OCR motion and bore shape must be considered in the case of calculation of oil film thickness for TPOCR.
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Chigali, Nikhil, Sai Rohith Bobba, K. Suvarna Vani, and S. Rajeswari. "OCR Assisted Translator." In 2020 7th International Conference on Smart Structures and Systems (ICSSS). IEEE, 2020. http://dx.doi.org/10.1109/icsss49621.2020.9202034.

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Genzel, Dmitriy, Ashok C. Popat, Nemanja Spasojevic, Michael Jahr, Andrew Senior, Eugene Ie, and Frank Yung-Fong Tang. "Translation-Inspired OCR." In 2011 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 2011. http://dx.doi.org/10.1109/icdar.2011.269.

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Zeng, Gangyan, Yuan Zhang, Yu Zhou, and Xiaomeng Yang. "Beyond OCR + VQA." In MM '21: ACM Multimedia Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3474085.3475606.

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Evershed, John, and Kent Fitch. "Correcting noisy OCR." In the First International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2595188.2595200.

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Hammadh Hassan, Mohamed, Zailan Arabee Bin Abdul Salam, and Kadhar Batcha Nowshath. "Dhivehi OCR Engine." In 2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE). IEEE, 2022. http://dx.doi.org/10.1109/icdcece53908.2022.9792674.

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Reports on the topic "OCR"

1

Kjersten, Brian. Arabic Optical Character Recognition (OCR) Evaluation in Order to Develop a Post-OCR Module. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada554465.

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Natarajan, Prem. Portable Language-Independent Adaptive Translation from OCR. Fort Belvoir, VA: Defense Technical Information Center, December 2008. http://dx.doi.org/10.21236/ada493372.

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Natarajan, Prem. Portable Language-Independent Adaptive Translation From OCR. Fort Belvoir, VA: Defense Technical Information Center, April 2009. http://dx.doi.org/10.21236/ada499805.

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Natarajan, Prem. Portable Language-Independent Adaptive Translation from OCR. Fort Belvoir, VA: Defense Technical Information Center, October 2009. http://dx.doi.org/10.21236/ada510335.

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Ma, Huanfeng, and David Doermann. Adaptive Hindi OCR Using Generalized Hausdorff Image Comparison. Fort Belvoir, VA: Defense Technical Information Center, August 2003. http://dx.doi.org/10.21236/ada455170.

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Natarajan, Prem. PLATO: Portable Language-Independent Adaptive Translation from OCR. Fort Belvoir, VA: Defense Technical Information Center, March 2008. http://dx.doi.org/10.21236/ada480485.

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Karagol-Ayan, Burcu, David Doermann, and Bonnie J. Dorr. Use of OCR for Rapid Construction of Bilingual Lexicons. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada455682.

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Wilson, Charles L., Jon Geist, Michael D. Garris, and Rama Chellapa. Design, integration, and evaluation of form-based handprint and OCR systems. Gaithersburg, MD: National Institute of Standards and Technology, 1996. http://dx.doi.org/10.6028/nist.ir.5932.

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Geist, Jon. Machine-assisted human classification of segmented characters for OCR testing and training. Gaithersburg, MD: National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.5105.

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Gomez-Bombarelli, Rafael. Global optimization of multicomponent oxide catalysts for OER/ORR. Office of Scientific and Technical Information (OSTI), May 2024. http://dx.doi.org/10.2172/2352284.

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