| |
Records |
Links |
|
Author  |
Volkmar Frinken; Francisco Zamora; Salvador España; Maria Jose Castro; Andreas Fischer; Horst Bunke |
|
| |
Title |
Long-Short Term Memory Neural Networks Language Modeling for Handwriting Recognition |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
701-704 |
|
| |
Keywords |
|
|
| |
Abstract |
Unconstrained handwritten text recognition systems maximize the combination of two separate probability scores. The first one is the observation probability that indicates how well the returned word sequence matches the input image. The second score is the probability that reflects how likely a word sequence is according to a language model. Current state-of-the-art recognition systems use statistical language models in form of bigram word probabilities. This paper proposes to model the target language by means of a recurrent neural network with long-short term memory cells. Because the network is recurrent, the considered context is not limited to a fixed size especially as the memory cells are designed to deal with long-term dependencies. In a set of experiments conducted on the IAM off-line database we show the superiority of the proposed language model over statistical n-gram models. |
|
| |
Address |
Tsukuba Science City, Japan |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FZE2012 |
Serial |
2052 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Volkmar Frinken; Andreas Fischer; Markus Baumgartner; Horst Bunke |
|
| |
Title |
Keyword spotting for self-training of BLSTM NN based handwriting recognition systems |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
| |
Volume |
47 |
Issue |
3 |
Pages |
1073-1082 |
|
| |
Keywords |
Document retrieval; Keyword spotting; Handwriting recognition; Neural networks; Semi-supervised learning |
|
| |
Abstract |
The automatic transcription of unconstrained continuous handwritten text requires well trained recognition systems. The semi-supervised paradigm introduces the concept of not only using labeled data but also unlabeled data in the learning process. Unlabeled data can be gathered at little or not cost. Hence it has the potential to reduce the need for labeling training data, a tedious and costly process. Given a weak initial recognizer trained on labeled data, self-training can be used to recognize unlabeled data and add words that were recognized with high confidence to the training set for re-training. This process is not trivial and requires great care as far as selecting the elements that are to be added to the training set is concerned. In this paper, we propose to use a bidirectional long short-term memory neural network handwritten recognition system for keyword spotting in order to select new elements. A set of experiments shows the high potential of self-training for bootstrapping handwriting recognition systems, both for modern and historical handwritings, and demonstrate the benefits of using keyword spotting over previously published self-training schemes. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.077; 602.101 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FFB2014 |
Serial |
2297 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes |
|
| |
Title |
Co-training for Handwritten Word Recognition |
Type |
Conference Article |
| |
Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
314-318 |
|
| |
Keywords |
|
|
| |
Abstract |
To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition. |
|
| |
Address |
Beijing, China |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FFB2011 |
Serial |
1789 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Volkmar Frinken; Andreas Fischer; Carlos David Martinez Hinarejos |
|
| |
Title |
Handwriting Recognition in Historical Documents using Very Large Vocabularies |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
2nd International Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
67-72 |
|
| |
Keywords |
|
|
| |
Abstract |
Language models are used in automatic transcription system to resolve ambiguities. This is done by limiting the vocabulary of words that can be recognized as well as estimating the n-gram probability of the words in the given text. In the context of historical documents, a non-unified spelling and the limited amount of written text pose a substantial problem for the selection of the recognizable vocabulary as well as the computation of the word probabilities. In this paper we propose for the transcription of historical Spanish text to keep the corpus for the n-gram limited to a sample of the target text, but expand the vocabulary with words gathered from external resources. We analyze the performance of such a transcription system with different sizes of external vocabularies and demonstrate the applicability and the significant increase in recognition accuracy of using up to 300 thousand external words. |
|
| |
Address |
Washington; USA; August 2013 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-1-4503-2115-0 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
HIP |
|
| |
Notes |
DAG; 600.056; 600.045; 600.061; 602.006; 602.101 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FFM2013 |
Serial |
2296 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Volkmar Frinken; Alicia Fornes; Josep Llados; Jean-Marc Ogier |
|
| |
Title |
Bidirectional Language Model for Handwriting Recognition |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
|
|
| |
Volume |
7626 |
Issue |
|
Pages |
611-619 |
|
| |
Keywords |
|
|
| |
Abstract |
In order to improve the results of automatically recognized handwritten text, information about the language is commonly included in the recognition process. A common approach is to represent a text line as a sequence. It is processed in one direction and the language information via n-grams is directly included in the decoding. This approach, however, only uses context on one side to estimate a word’s probability. Therefore, we propose a bidirectional recognition in this paper, using distinct forward and a backward language models. By combining decoding hypotheses from both directions, we achieve a significant increase in recognition accuracy for the off-line writer independent handwriting recognition task. Both language models are of the same type and can be estimated on the same corpus. Hence, the increase in recognition accuracy comes without any additional need for training data or language modeling complexity. |
|
| |
Address |
Japan |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
SSPR&SPR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FFL2012 |
Serial |
2057 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Veronica Romero; Emilio Granell; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
|
| |
Title |
Information Extraction in Handwritten Marriage Licenses Books |
Type |
Conference Article |
| |
Year |
2019 |
Publication |
5th International Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
66-71 |
|
| |
Keywords |
|
|
| |
Abstract |
Handwritten marriage licenses books are characterized by a simple structure of the text in the records with an evolutionary vocabulary, mainly composed of proper names that change along the time. This distinct vocabulary makes automatic transcription and semantic information extraction difficult tasks. Previous works have shown that the use of category-based language models and a Grammatical Inference technique known as MGGI can improve the accuracy of these
tasks. However, the application of the MGGI algorithm requires an a priori knowledge to label the words of the training strings, that is not always easy to obtain. In this paper we study how to automatically obtain the information required by the MGGI algorithm using a technique based on Confusion Networks. Using the resulting language model, full handwritten text recognition and information extraction experiments have been carried out with results supporting the proposed approach. |
|
| |
Address |
Sydney; Australia; September 2019 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
HIP |
|
| |
Notes |
DAG; 600.140; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RGF2019 |
Serial |
3352 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados |
|
| |
Title |
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition |
Type |
Journal Article |
| |
Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
| |
Volume |
46 |
Issue |
6 |
Pages |
1658-1669 |
|
| |
Keywords |
|
|
| |
Abstract |
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. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier Science Inc. New York, NY, USA |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0031-3203 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.045; 602.006; 605.203 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RFS2013 |
Serial |
2298 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
|
| |
Title |
Information Extraction in Handwritten Marriage Licenses Books Using the MGGI Methodology |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
8th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
| |
Volume |
10255 |
Issue |
|
Pages |
287-294 |
|
| |
Keywords |
Handwritten Text Recognition; Information extraction; Language modeling; MGGI; Categories-based language model |
|
| |
Abstract |
Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demographic and genealogical research. For example, marriage license books have been used for centuries by ecclesiastical and secular institutions to register marriages. These books follow a simple structure of the text in the records with a evolutionary vocabulary, mainly composed of proper names that change along the time. This distinct vocabulary makes automatic transcription and semantic information extraction difficult tasks. In previous works we studied the use of category-based language models and how a Grammatical Inference technique known as MGGI could improve the accuracy of these tasks. In this work we analyze the main causes of the semantic errors observed in previous results and apply a better implementation of the MGGI technique to solve these problems. Using the resulting language model, transcription and information extraction experiments have been carried out, and the results support our proposed approach. |
|
| |
Address |
Faro; Portugal; June 2017 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
L.A. Alexandre; J.Salvador Sanchez; Joao M. F. Rodriguez |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-319-58837-7 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
| |
Notes |
DAG; 602.006; 600.097; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RFV2017 |
Serial |
2952 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
|
| |
Title |
Using the MGGI Methodology for Category-based Language Modeling in Handwritten Marriage Licenses Books |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
15th international conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Handwritten marriage licenses books have been used for centuries by ecclesiastical and secular institutions to register marriages. The information contained in these historical documents is useful for demography studies and
genealogical research, among others. Despite the generally simple structure of the text in these documents, automatic transcription and semantic information extraction is difficult due to the distinct and evolutionary vocabulary, which is composed mainly of proper names that change along the time. In previous
works we studied the use of category-based language models to both improve the automatic transcription accuracy and make easier the extraction of semantic information. Here we analyze the main causes of the semantic errors observed in previous results and apply a Grammatical Inference technique known as MGGI to improve the semantic accuracy of the language model obtained. Using this language model, full handwritten text recognition experiments have been carried out, with results supporting the interest of the proposed approach. |
|
| |
Address |
Shenzhen; China; October 2016 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICFHR |
|
| |
Notes |
DAG; 600.097; 602.006 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RFV2016 |
Serial |
2909 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta |
|
| |
Title |
The ICDAR/GREC 2013 Music Scores Competition on Staff Removal |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Competition; Music scores; Staff Removal |
|
| |
Abstract |
The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. |
|
| |
Address |
Bethlehem; PA; USA; August 2013 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
GREC |
|
| |
Notes |
DAG; 600.045; 600.061 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ KFV2013 |
Serial |
2337 |
|
| Permanent link to this record |
