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Author |
Lluis Gomez |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Perceptual Organization for Text Extraction in Natural Scenes |
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Report |
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Year |
2012 |
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CVC Technical Report |
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173 |
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Bellaterra |
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Master's thesis |
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Admin @ si @ Gom2012 |
Serial |
2309 |
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Author |
Albert Gordo |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
A Cyclic Page Layout Descriptor for Document Classification & Retrieval |
Type |
Report |
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Year |
2009 |
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CVC Technical Report |
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128 |
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Corporate Author |
Computer Vision Center |
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Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC;DAG |
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Admin @ si @ Gor2009 |
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2387 |
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Author |
Jaume Gibert |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
Learning structural representations and graph matching paradigms in the context of object recognition |
Type |
Report |
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2009 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
CVC Technical Report |
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143 |
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Computer Vision Center |
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Master's thesis |
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DAG |
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Admin @ si @ Gib2009 |
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2397 |
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Author |
Farshad Nourbakhsh |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
Colour logo recognition |
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Report |
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2009 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
CVC Technical Report |
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145 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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DAG |
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Admin @ si @ Nou2009 |
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2399 |
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Author |
Nuria Cirera |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
Recognition of Handwritten Historical Documents |
Type |
Report |
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Year |
2012 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
CVC Technical Report |
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174 |
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DAG |
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no |
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Admin @ si @ Cir2012 |
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2416 |
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Author |
Marçal Rusiñol; Josep Llados |
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Title |
Flowchart Recognition in Patent Information Retrieval |
Type |
Book Chapter |
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Year |
2017 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Current Challenges in Patent Information Retrieval |
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37 |
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351-368 |
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Springer Berlin Heidelberg |
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M. Lupu; K. Mayer; N. Kando; A.J. Trippe |
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DAG; 600.097; 600.121 |
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no |
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Call Number |
Admin @ si @ RuL2017 |
Serial |
2896 |
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Permanent link to this record |
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Author |
Beata Megyesi; Bernhard Esslinger; Alicia Fornes; Nils Kopal; Benedek Lang; George Lasry; Karl de Leeuw; Eva Pettersson; Arno Wacker; Michelle Waldispuhl |
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Title |
Decryption of historical manuscripts: the DECRYPT project |
Type |
Journal Article |
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Year |
2020 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Cryptologia |
Abbreviated Journal |
CRYPT |
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Volume |
44 |
Issue |
6 |
Pages |
545-559 |
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automatic decryption; cipher collection; historical cryptology; image transcription |
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Abstract |
Many historians and linguists are working individually and in an uncoordinated fashion on the identification and decryption of historical ciphers. This is a time-consuming process as they often work without access to automatic methods and processes that can accelerate the decipherment. At the same time, computer scientists and cryptologists are developing algorithms to decrypt various cipher types without having access to a large number of original ciphertexts. In this paper, we describe the DECRYPT project aiming at the creation of resources and tools for historical cryptology by bringing the expertise of various disciplines together for collecting data, exchanging methods for faster progress to transcribe, decrypt and contextualize historical encrypted manuscripts. We present our goals and work-in progress of a general approach for analyzing historical encrypted manuscripts using standardized methods and a new set of state-of-the-art tools. We release the data and tools as open-source hoping that all mentioned disciplines would benefit and contribute to the research infrastructure of historical cryptology. |
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DAG; 600.140; 600.121 |
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Admin @ si @ MEF2020 |
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3347 |
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Author |
Marçal Rusiñol; Lluis Pere de las Heras; Joan Mas; Oriol Ramos Terrades; Dimosthenis Karatzas; Anjan Dutta; Gemma Sanchez; Josep Llados |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
CVC-UAB's participation in the Flowchart Recognition Task of CLEF-IP 2012 |
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Conference Article |
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2012 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Conference and Labs of the Evaluation Forum |
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Roma |
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CLEF |
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DAG |
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Admin @ si @ RHM2012 |
Serial |
2072 |
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Permanent link to this record |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Recognition of Multi-oriented Touching Characters in Graphical Documents |
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Conference Article |
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Year |
2008 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, |
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16 |
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297–304 |
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ICVGIP ’08 |
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DAG @ dag @ RPL2008c |
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1080 |
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Permanent link to this record |
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Author |
Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez |
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Title |
Computer Vision in Vehicle Technology: Land, Sea & Air |
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Book Whole |
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Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Computer Vision in Vehicle Technology: Land, Sea & Air |
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A unified view of the use of computer vision technology for different types of vehicles
Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment).
The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. |
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978-1-118-86807-2 |
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Admin @ si @ LIP2017b |
Serial |
3049 |
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Permanent link to this record |