12,995 research outputs found
Transcribing a 17th-century botanical manuscript: Longitudinal evaluation of document layout detection and interactive transcription
[EN] We present a process for cost-effective transcription of cursive handwritten text
images that has been tested on a 1,000-page 17th-century book about botanical
species. The process comprised two main tasks, namely: (1) preprocessing: page
layout analysis, text line detection, and extraction; and (2) transcription of the
extracted text line images. Both tasks were carried out with semiautomatic pro-
cedures, aimed at incrementally minimizing user correction effort, by means of
computer-assisted line detection and interactive handwritten text recognition
technologies. The contribution derived from this work is three-fold. First, we
provide a detailed human-supervised transcription of a relatively large historical
handwritten book, ready to be searchable, indexable, and accessible to cultural
heritage scholars as well as the general public. Second, we have conducted the
first longitudinal study to date on interactive handwriting text recognition, for
which we provide a very comprehensive user assessment of the real-world per-
formance of the technologies involved in this work. Third, as a result of this
process, we have produced a detailed transcription and document layout infor-
mation (i.e. high-quality labeled data) ready to be used by researchers working on
automated technologies for document analysis and recognition.This work is supported by the European Commission through the EU projects HIMANIS (JPICH program, Spanish, grant Ref. PCIN-2015-068) and READ (Horizon-2020 program, grant Ref. 674943); and the Universitat Politecnica de Valencia (grant number SP20130189). This work was also part of the Valorization and I+D+i Resources program of VLC/CAMPUS and has been funded by the Spanish MECD as part of the International Excellence Campus program.Toselli, AH.; Leiva, LA.; Bordes-Cabrera, I.; Hernández-Tornero, C.; Bosch Campos, V.; Vidal, E. (2018). Transcribing a 17th-century botanical manuscript: Longitudinal evaluation of document layout detection and interactive transcription. Digital Scholarship in the Humanities. 33(1):173-202. https://doi.org/10.1093/llc/fqw064S173202331Bazzi, I., Schwartz, R., & Makhoul, J. (1999). An omnifont open-vocabulary OCR system for English and Arabic. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(6), 495-504. doi:10.1109/34.771314Causer, T., Tonra, J., & Wallace, V. (2012). Transcription maximized; expense minimized? Crowdsourcing and editing The Collected Works of Jeremy Bentham*. Literary and Linguistic Computing, 27(2), 119-137. doi:10.1093/llc/fqs004Ramel, J. Y., Leriche, S., Demonet, M. L., & Busson, S. (2007). User-driven page layout analysis of historical printed books. International Journal of Document Analysis and Recognition (IJDAR), 9(2-4), 243-261. doi:10.1007/s10032-007-0040-6Romero, V., Fornés, A., Serrano, N., Sánchez, J. A., Toselli, A. H., Frinken, V., … Lladós, J. (2013). The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition. Pattern Recognition, 46(6), 1658-1669. doi:10.1016/j.patcog.2012.11.024Romero, V., Toselli, A. H., & Vidal, E. (2012). Multimodal Interactive Handwritten Text Transcription. Series in Machine Perception and Artificial Intelligence. doi:10.1142/8394Toselli, A. H., Romero, V., Pastor, M., & Vidal, E. (2010). Multimodal interactive transcription of text images. Pattern Recognition, 43(5), 1814-1825. doi:10.1016/j.patcog.2009.11.019Toselli, A. H., Vidal, E., Romero, V., & Frinken, V. (2016). HMM word graph based keyword spotting in handwritten document images. Information Sciences, 370-371, 497-518. doi:10.1016/j.ins.2016.07.063Bunke, H., Bengio, S., & Vinciarelli, A. (2004). Offline recognition of unconstrained handwritten texts using HMMs and statistical language models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6), 709-720. doi:10.1109/tpami.2004.1
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition
NOTICE: this is the author’s version of a work that was accepted for publication in Pattern Recognition. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern RecognitionVolume 46, Issue 6, June 2013, Pages 1658–1669
DOI: 10.1016/j.patcog.2012.11.024[EN] Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. © 2012 Elsevier Ltd. All rights reserved.Work supported by the EC (FEDER/FSE) and the Spanish MEC/MICINN under the MIPRCV ‘‘Consolider Ingenio 2010’’ program (CSD2007-00018), MITTRAL (TIN2009-14633-C03-01) and KEDIHC ((TIN2009-14633-C03-03) projects. This work has been partially supported by the European Research Council Advanced Grant (ERC-2010-AdG-20100407: 269796-5CofM) and the European seventh framework project (FP7-PEOPLE-2008-IAPP: 230653-ADAO). Also supported by the Generalitat Valenciana under grant Prometeo/2009/014 and FPU AP2007-02867, and by the Universitat Politecnica de Val encia (PAID-05-11). We would also like to thank the Center for Demographic Studies (UAB) and
the Cathedral of Barcelona.Romero Gómez, V.; Fornés, A.; Serrano Martínez-Santos, N.; Sánchez Peiró, JA.; Toselli ., AH.; Frinken, V.; Vidal, E.... (2013). The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition. Pattern Recognition. 46(6):1658-1669. https://doi.org/10.1016/j.patcog.2012.11.024S1658166946
Document segmentation using Relative Location Features
[ES] Presentamos un método genérico para análisis de layout ideado para trabajar sobre documentos con
layouts Manhattan y no-Manhattan. Proponemos la combinación de Relative Location Features junto
con características de textura para codificar las relaciones entre las diferentes clases de entidades.
Usando estas características construimos un Conditional Random Field que nos permite estimar el
mejor etiquetado en términos de minimización de energía. Los experimentos realizados sobre ambos
tipos de documentos demuestran que la utilización de Relative Location Features ayuda a mejorar los
resultados de la segmentación en documentos altamente estructurados, así como ofrecer resultados a
la altura del estado del arte sobre documentos sin una estructura aparente.[EN] We present a generic layout analysis method devised to work in documents with both Manhattan and
non-Mahnattan layouts. We propose to use Relative Location features combined with texture features
to encode the relationships between the different class entities. Using these features we build a
Conditional Random Field framework that allow us to obtain the best class configuration of an image in
terms of energy minimization. The conducted experiments with Manhattan and non-Manhattan layouts
prove that using Relative Location Features improves the segmentation results on highly structured
documents, as well as results up to the state of the art on documents weakly structured.Cruz Fernández, F. (2012). Document segmentation using Relative Location Features. http://hdl.handle.net/10251/19219Archivo delegad
Occode: an end-to-end machine learning pipeline for transcription of historical population censuses
Machine learning approaches achieve high accuracy for text recognition and
are therefore increasingly used for the transcription of handwritten historical
sources. However, using machine learning in production requires a streamlined
end-to-end machine learning pipeline that scales to the dataset size, and a
model that achieves high accuracy with few manual transcriptions. In addition,
the correctness of the model results must be verified. This paper describes our
lessons learned developing, tuning, and using the Occode end-to-end machine
learning pipeline for transcribing 7,3 million rows with handwritten occupation
codes in the Norwegian 1950 population census. We achieve an accuracy of 97%
for the automatically transcribed codes, and we send 3% of the codes for manual
verification. We verify that the occupation code distribution found in our
result matches the distribution found in our training data which should be
representative for the census as a whole. We believe our approach and lessons
learned are useful for other transcription projects that plan to use machine
learning in production. The source code is available at:
https://github.com/uit-hdl/rhd-code
Mathematical Expression Recognition based on Probabilistic Grammars
[EN] Mathematical notation is well-known and used all over the
world. Humankind has evolved from simple methods representing
countings to current well-defined math notation able to account for
complex problems. Furthermore, mathematical expressions constitute a
universal language in scientific fields, and many information
resources containing mathematics have been created during the last
decades. However, in order to efficiently access all that information,
scientific documents have to be digitized or produced directly in
electronic formats.
Although most people is able to understand and produce mathematical
information, introducing math expressions into electronic devices
requires learning specific notations or using editors. Automatic
recognition of mathematical expressions aims at filling this gap
between the knowledge of a person and the input accepted by
computers. This way, printed documents containing math expressions
could be automatically digitized, and handwriting could be used for
direct input of math notation into electronic devices.
This thesis is devoted to develop an approach for mathematical
expression recognition. In this document we propose an approach for
recognizing any type of mathematical expression (printed or
handwritten) based on probabilistic grammars. In order to do so, we
develop the formal statistical framework such that derives several
probability distributions. Along the document, we deal with the
definition and estimation of all these probabilistic sources of
information. Finally, we define the parsing algorithm that globally
computes the most probable mathematical expression for a given input
according to the statistical framework.
An important point in this study is to provide objective performance
evaluation and report results using public data and standard
metrics. We inspected the problems of automatic evaluation in this
field and looked for the best solutions. We also report several
experiments using public databases and we participated in several
international competitions. Furthermore, we have released most of the
software developed in this thesis as open source.
We also explore some of the applications of mathematical expression
recognition. In addition to the direct applications of transcription
and digitization, we report two important proposals. First, we
developed mucaptcha, a method to tell humans and computers apart by
means of math handwriting input, which represents a novel application
of math expression recognition. Second, we tackled the problem of
layout analysis of structured documents using the statistical
framework developed in this thesis, because both are two-dimensional
problems that can be modeled with probabilistic grammars.
The approach developed in this thesis for mathematical expression
recognition has obtained good results at different levels. It has
produced several scientific publications in international conferences
and journals, and has been awarded in international competitions.[ES] La notación matemática es bien conocida y se utiliza en todo el
mundo. La humanidad ha evolucionado desde simples métodos para
representar cuentas hasta la notación formal actual capaz de modelar
problemas complejos. Además, las expresiones matemáticas constituyen
un idioma universal en el mundo científico, y se han creado muchos
recursos que contienen matemáticas durante las últimas décadas. Sin
embargo, para acceder de forma eficiente a toda esa información, los
documentos científicos han de ser digitalizados o producidos
directamente en formatos electrónicos.
Aunque la mayoría de personas es capaz de entender y producir
información matemática, introducir expresiones matemáticas en
dispositivos electrónicos requiere aprender notaciones especiales o
usar editores. El reconocimiento automático de expresiones matemáticas
tiene como objetivo llenar ese espacio existente entre el conocimiento
de una persona y la entrada que aceptan los ordenadores. De este modo,
documentos impresos que contienen fórmulas podrían digitalizarse
automáticamente, y la escritura se podría utilizar para introducir
directamente notación matemática en dispositivos electrónicos.
Esta tesis está centrada en desarrollar un método para reconocer
expresiones matemáticas. En este documento proponemos un método para
reconocer cualquier tipo de fórmula (impresa o manuscrita) basado en
gramáticas probabilísticas. Para ello, desarrollamos el marco
estadístico formal que deriva varias distribuciones de probabilidad. A
lo largo del documento, abordamos la definición y estimación de todas
estas fuentes de información probabilística. Finalmente, definimos el
algoritmo que, dada cierta entrada, calcula globalmente la expresión
matemática más probable de acuerdo al marco estadístico.
Un aspecto importante de este trabajo es proporcionar una evaluación
objetiva de los resultados y presentarlos usando datos públicos y
medidas estándar. Por ello, estudiamos los problemas de la evaluación
automática en este campo y buscamos las mejores soluciones. Asimismo,
presentamos diversos experimentos usando bases de datos públicas y
hemos participado en varias competiciones internacionales. Además,
hemos publicado como código abierto la mayoría del software
desarrollado en esta tesis.
También hemos explorado algunas de las aplicaciones del reconocimiento
de expresiones matemáticas. Además de las aplicaciones directas de
transcripción y digitalización, presentamos dos propuestas
importantes. En primer lugar, desarrollamos mucaptcha, un método para
discriminar entre humanos y ordenadores mediante la escritura de
expresiones matemáticas, el cual representa una novedosa aplicación
del reconocimiento de fórmulas. En segundo lugar, abordamos el
problema de detectar y segmentar la estructura de documentos
utilizando el marco estadístico formal desarrollado en esta tesis,
dado que ambos son problemas bidimensionales que pueden modelarse con
gramáticas probabilísticas.
El método desarrollado en esta tesis para reconocer expresiones
matemáticas ha obtenido buenos resultados a diferentes niveles. Este
trabajo ha producido varias publicaciones en conferencias
internacionales y revistas, y ha sido premiado en competiciones
internacionales.[CA] La notació matemàtica és ben coneguda i s'utilitza a tot el món. La
humanitat ha evolucionat des de simples mètodes per representar
comptes fins a la notació formal actual capaç de modelar
problemes complexos. A més, les expressions matemàtiques
constitueixen un idioma universal al món científic, i s'han creat
molts recursos que contenen matemàtiques durant les últimes
dècades. No obstant això, per accedir de forma eficient a tota
aquesta informació, els documents científics han de ser
digitalitzats o produïts directament en formats electrònics.
Encara que la majoria de persones és capaç d'entendre i produir
informació matemàtica, introduir expressions matemàtiques en
dispositius electrònics requereix aprendre notacions especials o usar
editors. El reconeixement automàtic d'expressions matemàtiques
té per objectiu omplir aquest espai existent entre el coneixement
d'una persona i l'entrada que accepten els ordinadors. D'aquesta
manera, documents impresos que contenen fórmules podrien
digitalitzar-se automàticament, i l'escriptura es podria utilitzar per
introduir directament notació matemàtica en dispositius electrònics.
Aquesta tesi està centrada en desenvolupar un mètode per reconèixer
expressions matemàtiques. En aquest document proposem un mètode per
reconèixer qualsevol tipus de fórmula (impresa o manuscrita) basat en
gramàtiques probabilístiques. Amb aquesta finalitat, desenvolupem el
marc estadístic formal que deriva diverses distribucions de
probabilitat. Al llarg del document, abordem la definició i estimació
de totes aquestes fonts d'informació probabilística. Finalment,
definim l'algorisme que, donada certa entrada, calcula globalment
l'expressió matemàtica més probable d'acord al marc estadístic.
Un aspecte important d'aquest treball és proporcionar una avaluació
objectiva dels resultats i presentar-los usant dades públiques i
mesures estàndard. Per això, estudiem els problemes de l'avaluació
automàtica en aquest camp i busquem les millors solucions. Així
mateix, presentem diversos experiments usant bases de dades públiques
i hem participat en diverses competicions internacionals. A més, hem
publicat com a codi obert la majoria del software desenvolupat en
aquesta tesi.
També hem explorat algunes de les aplicacions del reconeixement
d'expressions matemàtiques. A més de les aplicacions directes de
transcripció i digitalització, presentem dues propostes
importants. En primer lloc, desenvolupem mucaptcha, un mètode per
discriminar entre humans i ordinadors mitjançant l'escriptura
d'expressions matemàtiques, el qual representa una nova aplicació del
reconeixement de fórmules. En segon lloc, abordem el problema de
detectar i segmentar l'estructura de documents utilitzant el marc
estadístic formal desenvolupat en aquesta tesi, donat que ambdós són
problemes bidimensionals que poden modelar-se amb gramàtiques
probabilístiques.
El mètode desenvolupat en aquesta tesi per reconèixer expressions
matemàtiques ha obtingut bons resultats a diferents nivells. Aquest
treball ha produït diverses publicacions en conferències
internacionals i revistes, i ha sigut premiat en competicions
internacionals.Álvaro Muñoz, F. (2015). Mathematical Expression Recognition based on Probabilistic Grammars [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/51665TESI
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Small and Large Cultures: Individuality, the Collective, Conformity and the Period of the Cold War
The Cold War is something I analyze in two parts. First, I examine its politics, including political literatures and cultures large and small that concentrate on central concerns of the Cold War. Second, I discuss small and minor literatures in the period of the Cold War in theory and practice, including examples from the Netherlands and Canada that are in the period of the Cold War but do not focus on it as its primary concern or theme. In these sections, I argue for the centrality of the tension between tyranny and liberty, individual and the group, conformity and nonconformity and related matters. The article ranges in the politics of the Cold War from the background of Marx and Mill though Churchill, Stalin, Truman, McCarthy to Russell, Grant and Ignatieff. In literature, that is the Cold War in ink, the essay analyzes Orwell’s essay on the nuclear bomb and his novels, Nineteen Eighty-four and Animal Farm as well as Miller’s play, The Crucible and a poem by Einstein on Russell. I concentrate on examples of Dutch fiction and their translation into English and a Canadian novel, The Weekend Man, by Richard B. Wright, because they are an element of “minority literatures.” Besides exploring the Cold War, I briefly examine theories of minor or small literatures, including some aspects of the views of Kafka, Deleuze and Guattari
A Multi-Decade Look at Black Female/White Male Interracial Marriages
abstract: The number of interracial marriages and multiracial individuals continues to increase rapidly in the United States (U.S. Census Bureau, 2010). Black Female (BF) /White Male (WM) marriages are increasing, but not as quickly as other interracial marriages (Wang, 2012) leaving this population void in social science literature available to social workers. Consequently, there is a lack of information available to understand factors that contribute to these couple identities and how they navigate in the monoracialized systems they encounter. This qualitative study explored how BF/WM partners married in different generational cohorts experience and navigate race and identity as a couple through video recorded interviews where couples shared their narrative as a dyad. The secondary data analyzed was originally collected through snowball and convenient sampling to find BF/WM married couples that were married different generational cohorts living in the Phoenix area. Couples were asked to respond to starter questions (Linhorst, 2002) that encouraged them to share experiences as a couple interacting with community, social, and family systems. Ecological systems framework and social construction were used to guide analysis. Results from the multimodal transcript analysis and detailed review of the video data found themes of invisibility of the couples' relationships from community and family. Differences between cohorts were identified with movement from separation of racial identities within the couple identity to an infusion of both identities represented within the couple. Additionally, insights into the benefits of videography as a data collection method and its usefulness in to connecting social work research to practice were identified and align with the NASW Cultural Competence standards (NASW, 2001).Dissertation/ThesisDoctoral Dissertation Social Work 201
Engaging an Unengaged Demographic: A Phenomenological Study of Christian Millennials’ Engagement with Religious and Nonreligious Memberships
Church membership is declining worldwide. Studies show that Millennials are less likely to belong to a church than previous generations. Even among churched Millennials, only 48% of church-attending Millennials are church members. Simultaneously, organizations such as health, fitness, and social clubs are seeing an increase in Millennial membership growth. Brand loyalty is high among Millennials, but church loyalty is low even among practicing Christian Millennials who attend church at least once per month. The purpose of this qualitative phenomenological study was to explore how practicing Christian Millennials understand the nature of engagement with church and nonreligious memberships and the factors that shape those commitments. Practicing Christian Millennials were generally defined as anyone born between 1981 and 1996 who self-identified as a Christian and attended a trinitarian Protestant church in the United States at least once per month. The methodology guiding this study was Husserl’s phenomenological approach to gaining insight into the phenomenon of Christian Millennials’ engagement rates with religious and nonreligious memberships
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