| |
Records |
Links |
|
Author |
H. Chouaib; Oriol Ramos Terrades; Salvatore Tabbone; F. Cloppet; N. Vincent |
|
| |
Title  |
Feature Selection Combining Genetic Algorithm and Adaboost Classifiers |
Type |
Conference Article |
| |
Year |
2008 |
Publication |
19th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1-4 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Tampa, Florida |
|
| |
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 |
ICPR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ CRT2008 |
Serial |
1872 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
|
| |
Title |
Feature Selection on Node Statistics Based Embedding of Graphs |
Type |
Journal Article |
| |
Year |
2012 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
|
| |
Volume |
33 |
Issue |
15 |
Pages |
1980–1990 |
|
| |
Keywords |
Structural pattern recognition; Graph embedding; Feature ranking; PCA; Graph classification |
|
| |
Abstract |
Representing a graph with a feature vector is a common way of making statistical machine learning algorithms applicable to the domain of graphs. Such a transition from graphs to vectors is known as graphembedding. A key issue in graphembedding is to select a proper set of features in order to make the vectorial representation of graphs as strong and discriminative as possible. In this article, we propose features that are constructed out of frequencies of node label representatives. We first build a large set of features and then select the most discriminative ones according to different ranking criteria and feature transformation algorithms. On different classification tasks, we experimentally show that only a small significant subset of these features is needed to achieve the same classification rates as competing to state-of-the-art methods. |
|
| |
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 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GVB2012b |
Serial |
1993 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mohamed Ali Souibgui; Alicia Fornes; Yousri Kessentini; Beata Megyesi |
|
| |
Title |
Few shots are all you need: A progressive learning approach for low resource handwritten text recognition |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
|
| |
Volume |
160 |
Issue |
|
Pages |
43-49 |
|
| |
Keywords |
|
|
| |
Abstract |
Handwritten text recognition in low resource scenarios, such as manuscripts with rare alphabets, is a challenging problem. In this paper, we propose a few-shot learning-based handwriting recognition approach that significantly reduces the human annotation process, by requiring only a few images of each alphabet symbols. The method consists of detecting all the symbols of a given alphabet in a textline image and decoding the obtained similarity scores to the final sequence of transcribed symbols. Our model is first pretrained on synthetic line images generated from an alphabet, which could differ from the alphabet of the target domain. A second training step is then applied to reduce the gap between the source and the target data. Since this retraining would require annotation of thousands of handwritten symbols together with their bounding boxes, we propose to avoid such human effort through an unsupervised progressive learning approach that automatically assigns pseudo-labels to the unlabeled data. The evaluation on different datasets shows that our model can lead to competitive results with a significant reduction in human effort. The code will be publicly available in the following repository: https://github.com/dali92002/HTRbyMatching |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier |
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; 600.121; 600.162; 602.230 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SFK2022 |
Serial |
3736 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
V. Poulain d'Andecy; Emmanuel Hartmann; Marçal Rusiñol |
|
| |
Title |
Field Extraction by hybrid incremental and a-priori structural templates |
Type |
Conference Article |
| |
Year |
2018 |
Publication |
13th IAPR International Workshop on Document Analysis Systems |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
251 - 256 |
|
| |
Keywords |
Layout Analysis; information extraction; incremental learning |
|
| |
Abstract |
In this paper, we present an incremental framework for extracting information fields from administrative documents. First, we demonstrate some limits of the existing state-of-the-art methods such as the delay of the system efficiency. This is a concern in industrial context when we have only few samples of each document class. Based on this analysis, we propose a hybrid system combining incremental learning by means of itf-df statistics and a-priori generic
models. We report in the experimental section our results obtained with a dataset of real invoices. |
|
| |
Address |
Viena; Austria; April 2018 |
|
| |
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 |
DAS |
|
| |
Notes |
DAG; 600.084; 600.129; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PHR2018 |
Serial |
3106 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; T.Benkhelfallah; V. Poulain d'Andecy |
|
| |
Title |
Field Extraction from Administrative Documents by Incremental Structural Templates |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1100 - 1104 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices. |
|
| |
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 |
1520-5363 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG; 600.56; 600.045; 605.203; 602.101 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RBP2013 |
Serial |
2346 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier |
|
| |
Title |
Filtrage de descripteurs locaux pour l'amélioration de la détection de documents |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
Colloque International Francophone sur l'Écrit et le Document |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Local descriptors; mobile capture; document matching; keypoint selection |
|
| |
Abstract |
In this paper we propose an effective method aimed at reducing the amount of local descriptors to be indexed in a document matching framework.In an off-line training stage, the matching between the model document and incoming images is computed retaining the local descriptors from the model that steadily produce good matches. We have evaluated this approach by using the ICDAR2015 SmartDOC dataset containing near 25000 images from documents to be captured by a mobile device. We have tested the performance of this filtering step by using ORB and SIFT local detectors and descriptors. The results show an important gain both in quality of the final matching as well as in time and space requirements. |
|
| |
Address |
Toulouse; France; March 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 |
CIFED |
|
| |
Notes |
DAG; 600.084; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RCO2016 |
Serial |
2755 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Horst Bunke; Enric Marti |
|
| |
Title |
Finding rotational symmetries by cyclic string matching |
Type |
Journal Article |
| |
Year |
1997 |
Publication |
Pattern recognition letters |
Abbreviated Journal |
PRL |
|
| |
Volume |
18 |
Issue |
14 |
Pages |
1435-1442 |
|
| |
Keywords |
Rotational symmetry; Reflectional symmetry; String matching |
|
| |
Abstract |
Symmetry is an important shape feature. In this paper, a simple and fast method to detect perfect and distorted rotational symmetries of 2D objects is described. The boundary of a shape is polygonally approximated and represented as a string. Rotational symmetries are found by cyclic string matching between two identical copies of the shape string. The set of minimum cost edit sequences that transform the shape string to a cyclically shifted version of itself define the rotational symmetry and its order. Finally, a modification of the algorithm is proposed to detect reflectional symmetries. Some experimental results are presented to show the reliability of the proposed algorithm |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier |
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;IAM; |
Approved |
no |
|
| |
Call Number |
IAM @ iam @ LBM1997a |
Serial |
1562 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Andres Mafla; Sounak Dey; Ali Furkan Biten; Lluis Gomez; Dimosthenis Karatzas |
|
| |
Title |
Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features |
Type |
Conference Article |
| |
Year |
2020 |
Publication |
IEEE Winter Conference on Applications of Computer Vision |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Text contained in an image carries high-level semantics that can be exploited to achieve richer image understanding. In particular, the mere presence of text provides strong guiding content that should be employed to tackle a diversity of computer vision tasks such as image retrieval, fine-grained classification, and visual question answering. In this paper, we address the problem of fine-grained classification and image retrieval by leveraging textual information along with visual cues to comprehend the existing intrinsic relation between the two modalities. The novelty of the proposed model consists of the usage of a PHOC descriptor to construct a bag of textual words along with a Fisher Vector Encoding that captures the morphology of text. This approach provides a stronger multimodal representation for this task and as our experiments demonstrate, it achieves state-of-the-art results on two different tasks, fine-grained classification and image retrieval. |
|
| |
Address |
Aspen; Colorado; USA; March 2020 |
|
| |
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 |
WACV |
|
| |
Notes |
DAG; 600.121; 600.129 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ MDB2020 |
Serial |
3334 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; Lluis Pere de las Heras; Oriol Ramos Terrades |
|
| |
Title |
Flowchart Recognition for Non-Textual Information Retrieval in Patent Search |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
Information Retrieval |
Abbreviated Journal |
IR |
|
| |
Volume |
17 |
Issue |
5-6 |
Pages |
545-562 |
|
| |
Keywords |
Flowchart recognition; Patent documents; Text/graphics separation; Raster-to-vector conversion; Symbol recognition |
|
| |
Abstract |
Relatively little research has been done on the topic of patent image retrieval and in general in most of the approaches the retrieval is performed in terms of a similarity measure between the query image and the images in the corpus. However, systems aimed at overcoming the semantic gap between the visual description of patent images and their conveyed concepts would be very helpful for patent professionals. In this paper we present a flowchart recognition method aimed at achieving a structured representation of flowchart images that can be further queried semantically. The proposed method was submitted to the CLEF-IP 2012 flowchart recognition task. We report the obtained results on this dataset. |
|
| |
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 |
1386-4564 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RHR2013 |
Serial |
2342 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; Josep Llados |
|
| |
Title |
Flowchart Recognition in Patent Information Retrieval |
Type |
Book Chapter |
| |
Year |
2017 |
Publication |
Current Challenges in Patent Information Retrieval |
Abbreviated Journal |
|
|
| |
Volume |
37 |
Issue |
|
Pages |
351-368 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
M. Lupu; K. Mayer; N. Kando; A.J. Trippe |
|
| |
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; 600.097; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RuL2017 |
Serial |
2896 |
|
| Permanent link to this record |
