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Author |
Anton Cervantes; Gemma Sanchez; Josep Llados; Agnes Borras; A. Rodriguez |
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Title |
Biometric Recognition Based on Line Shape Descriptors |
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Conference Article |
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Year |
2005 |
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Sixth IAPR International Workshop on Graphics Recognition (GREC 2005) |
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335–344 |
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Hong Kong (China) |
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DAG @ dag @ CSL2005 |
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596 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
An Incremental Parser to Recognize Diagram Symbols and Gestures represented by Adjacency Grammars |
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Miscellaneous |
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Year |
2005 |
Publication |
Sixth IAPR International Workshop on Graphics Recognition (GREC 2005), 229–237 |
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Hong Kong (China) |
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DAG @ dag @ MSL2005b |
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611 |
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Author |
N. Zakaria; Jean-Marc Ogier; Josep Llados |
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Title |
On-line Graphics Recognition based on Invariant Spatio-Sequential Descriptor: Fuzzy Matrix |
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Miscellaneous |
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2005 |
Publication |
Sixth IAPR International Workshop on Graphics Recognition (GREC 2005), 248–259 |
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Hong Kong (China) |
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DAG |
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Call Number |
DAG @ dag @ YFY2005b |
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622 |
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Author |
W. Liu; Josep Llados |
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Title |
Graphics Recognition. Ten Years Review and Future Perspectives |
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Book Whole |
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Year |
2006 |
Publication |
6th International Workshop |
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3926 |
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Hong Kong (China) |
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GREC |
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DAG |
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DAG @ dag @ LiL2006 |
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800 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Primitive Segmentation in Old Handwritten Music Scores |
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Miscellaneous |
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Year |
2005 |
Publication |
6th IAPR International Workshop on Graphics Recognition (GREC 2005) |
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Hong Kong, Hong Kong SAR (China) |
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DAG |
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DAG @ dag @ FLS2005a |
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584 |
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Author |
Lluis Gomez; Y. Patel; Marçal Rusiñol; C.V. Jawahar; Dimosthenis Karatzas |
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Title |
Self‐supervised learning of visual features through embedding images into text topic spaces |
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Conference Article |
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2017 |
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30th IEEE Conference on Computer Vision and Pattern Recognition |
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End-to-end training from scratch of current deep architectures for new computer vision problems would require Imagenet-scale datasets, and this is not always possible. In this paper we present a method that is able to take advantage of freely available multi-modal content to train computer vision algorithms without human supervision. We put forward the idea of performing self-supervised learning of visual features by mining a large scale corpus of multi-modal (text and image) documents. We show that discriminative visual features can be learnt efficiently by training a CNN to predict the semantic context in which a particular image is more probable to appear as an illustration. For this we leverage the hidden semantic structures discovered in the text corpus with a well-known topic modeling technique. Our experiments demonstrate state of the art performance in image classification, object detection, and multi-modal retrieval compared to recent self-supervised or natural-supervised approaches. |
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Honolulu; Hawaii; July 2017 |
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CVPR |
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DAG; 600.084; 600.121 |
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Admin @ si @ GPR2017 |
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2889 |
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Author |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) |
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Title |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 |
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Book Whole |
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2022 |
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Frontiers in Handwriting Recognition. |
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13639 |
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ICFHR 2022, Hyderabad, India, December 4–7, 2022 |
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Springer |
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Utkarsh Porwal; Alicia Fornes; Faisal Shafait |
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978-3-031-21648-0 |
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ICFHR |
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DAG |
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Admin @ si @ PFS2022 |
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3809 |
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Author |
Dimosthenis Karatzas;Ch. Lioutas |
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Title |
Software Package Development for Electron Diffraction Image Analysis |
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Conference Article |
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Year |
1998 |
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Proceedings of the XIV Solid State Physics National Conference |
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Ioannina, Greece |
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IAM @ iam @ KaL1998 |
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2045 |
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Author |
Anjan Dutta; Umapada Pal; Alicia Fornes; Josep Llados |
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Title |
An Efficient Staff Removal Technique from Printed Musical Documents |
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Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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1965–1968 |
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Staff removal is an important preprocessing step of the Optical Music Recognition (OMR). The process aims to remove the stafflines from a musical document and retain only the musical symbols, later these symbols are used effectively to identify the music information. This paper proposes a simple but robust method to remove stafflines from printed musical scores. In the proposed methodology we have considered a staffline segment as a horizontal linkage of vertical black runs with uniform height. We have used the neighbouring properties of a staffline segment to validate it as a true segment. We have considered the dataset along with the deformations described in for evaluation purpose. From experimentation we have got encouraging results. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG @ dag @ DPF2010 |
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1420 |
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Author |
Alicia Fornes; Sergio Escalera; Josep Llados; Ernest Valveny |
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Title |
Symbol Classification using Dynamic Aligned Shape Descriptor |
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Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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1957–1960 |
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Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we propose a new descriptor and distance computation for coping with the problem of symbol recognition in the domain of Graphical Document Image Analysis. The proposed D-Shape descriptor encodes the arrangement information of object parts in a circular structure, allowing different levels of distortion. The classification is performed using a cyclic Dynamic Time Warping based method, allowing distortions and rotation. The methodology has been validated on different data sets, showing very high recognition rates. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG; HUPBA; MILAB |
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BCNPCL @ bcnpcl @ FEL2010 |
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1421 |
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