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  • Search: subject:"Optical character recognition"
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Year of publication
Subject
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Optical Character Recognition 6 Optical character recognition 6 optical character recognition 4 OCR 3 Data collection 2 Digital libraries 2 Digitalisierung 2 Displays 2 Image databases 2 Smart metering 2 Text recognition 2 Theorie 2 Theory 2 AGRICULTURE 1 Archives 1 Bildverarbeitung 1 CNN 1 COMMUNITIES 1 Check Processing 1 Co-Occurrence 1 Computerized method 1 Computerunterstützung 1 Convoluted Neural Networks 1 DATA ENTRY 1 DIGITAL 1 DIGITAL DIVIDE 1 DRINKING WATER 1 DWT 1 Data Mining 1 Data mining 1 Datenprüfung 1 Deep Learning 1 Denoise 1 Digital history 1 Digitization 1 Distance Transform 1 Document Imaging 1 Document management 1 Dokumentanalyse 1 Dokumentenmanagement 1
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Online availability
All
Free 8 Undetermined 8 CC license 4
Type of publication
All
Article 15 Book / Working Paper 3
Type of publication (narrower categories)
All
Article in journal 5 Aufsatz in Zeitschrift 5 research-article 3 Article 1 Hochschulschrift 1 Thesis 1
Language
All
English 14 Undetermined 3 German 1
Author
All
Kanagarathinam, Karthick 2 Sekar, Kavaskar 2 Afzal, Muhammad Zeshan 1 Altieri, Elena 1 Anand, R. 1 Blanke, Tobias 1 Bryant, Michael 1 Burchardt, Jørgen 1 Cheng, Li 1 Das, Supratim 1 Dengel, Andreas 1 Eichenberger-Liwicki, Marcus 1 Fritsche, Ulrich 1 Gooding, Paul 1 Gupta, Amar 1 Hedges, Mark 1 Härdle, Wolfgang 1 Kouritzin, Michael A. 1 Kumar, D. Pradeep 1 Moro, Rouslan A. 1 Nasipuri, Mita 1 Neal, Christopher 1 Newton, Fraser 1 Nockels, Joseph 1 Palacios, Rafael 1 Palm, Günther 1 Prabhakar, C. J. 1 Sabeenian, R. S. 1 Sarkar, Ram 1 Schmidt, Miriam 1 Schramm, Florian 1 Schwenker, Friedhelm 1 Schäfer, Dorothea 1 Shanthi, T. 1 Shetty, Chetan 1 Singh, Pawan Kumar 1 Sowmya, B.J. 1 Spoerer, Mark 1 Srinivasa, K.G. 1 Terras, Melissa 1
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Institution
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Sloan School of Management, Massachusetts Institute of Technology (MIT) 1 Sonderforschungsbereich 649: Ökonomisches Risiko, Wirtschaftswissenschaftliche Fakultät 1 Technische Universität Kaiserslautern 1 Technische Universität Kaiserslautern / Fachbereich Maschinenbau und Verfahrenstechnik 1
Published in...
All
International Journal of Computer Vision and Image Processing (IJCVIP) 2 Jahrbuch für Wirtschaftsgeschichte 2 Journal of Documentation 2 Computational Statistics 1 Computational Statistics & Data Analysis 1 Development Outreach 1 Energy Reports 1 Energy reports 1 Informatik 1 International Journal of Applied Evolutionary Computation (IJAEC) 1 International Journal of Mobile Computing and Multimedia Communications (IJMCMC) 1 International journal of intelligent enterprise 1 SFB 649 Discussion Papers 1 WPg : Kompetenz schafft Vertrauen 1 Working papers / Sloan School of Management, Massachusetts Institute of Technology (MIT) 1
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Source
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Other ZBW resources 7 ECONIS (ZBW) 6 RePEc 4 EconStor 1
Showing 11 - 18 of 18
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Scale Space Co-Occurrence HOG Features for Word Spotting in Handwritten Document Images
Thontadari, C.; Prabhakar, C. J. - In: International Journal of Computer Vision and Image … 6 (2016) 2, pp. 71-86
In this paper, the authors proposed a Scale Space Co-occurrence Histograms of Oriented Gradients method (SS Co-HOG) for retrieving words from digitized handwritten documents. The poor performance of HOG based word spotting in handwritten documents is due to that HOG ignores spatial information...
Persistent link: https://www.econbiz.de/10012043820
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Deep learning in space and time for document image processing
Afzal, Muhammad Zeshan - 2016
Persistent link: https://www.econbiz.de/10011753911
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Development Marketplace Helps Scale up Grassroots Innovation that Reduces Poverty
Altieri, Elena; Neal, Christopher - In: Development Outreach 11 (2009) 1, pp. 30-32
This article presents examples of grassroots aid projects and programs that delivers results, within the framework of the Development Marketplace. It discusses the extent to which such community-based efforts can be replicated.
Persistent link: https://www.econbiz.de/10015360057
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A graph theoretic approach to simulation and classification
Kouritzin, Michael A.; Newton, Fraser; Wu, Biao - In: Computational Statistics & Data Analysis 70 (2014) C, pp. 281-294
optical character recognition are now given within. …
Persistent link: https://www.econbiz.de/10011056448
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Cover Image
Spectral graph features for the classification of graphs and graph sequences
Schmidt, Miriam; Palm, Günther; Schwenker, Friedhelm - In: Computational Statistics 29 (2014) 1, pp. 65-80
performances of the different feature types is evaluated on two data sets: first a benchmark data set for optical character … recognition, where the extracted eigenvalues were utilized as feature vectors for multi-class classification using support vector …
Persistent link: https://www.econbiz.de/10010998507
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Predicting Bankruptcy with Support Vector Machines
Härdle, Wolfgang; Moro, Rouslan A.; Schäfer, Dorothea - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2005
The purpose of this work is to introduce one of the most promising among recently developed statistical techniques – the support vector machine (SVM) – to corporate bankruptcy analysis. An SVM is implemented for analysing such predictors as financial ratios. A method of adapting it to...
Persistent link: https://www.econbiz.de/10005489966
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Open source optical character recognition for historical research
Blanke, Tobias; Bryant, Michael; Hedges, Mark - In: Journal of Documentation 68 (2012) 5, pp. 659-683
Purpose – This paper aims to present an evaluation of open source OCR for supporting research on material in small‐ to medium‐scale historical archives. Design/methodology/approach – The approach was to develop a workflow engine to support the easy customisation of the OCR process...
Persistent link: https://www.econbiz.de/10014853558
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Training Neural Networks for Reading Handwritten Amounts on Checks
Gupta, Amar; Palacios, Rafael - Sloan School of Management, Massachusetts Institute of … - 2002
While reading handwritten text accurately is a difficult task for computers, the conversion of handwritten papers into digital format is necessary for automatic processing. Since most bank checks are handwritten, the number of checks is very high, and manual processing involves significant...
Persistent link: https://www.econbiz.de/10005574574
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