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Author |
Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny |


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Title |
A polar-based logo representation based on topological and colour features |
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Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
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341–348 |
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In this paper, we propose a novel rotation and scale invariant method for colour logo retrieval and classification, which involves performing a simple colour segmentation and subsequently describing each of the resultant colour components based on a set of topological and colour features. A polar representation is used to represent the logo and the subsequent logo matching is based on Cyclic Dynamic Time Warping (CDTW). We also show how combining information about the global distribution of the logo components and their local neighbourhood using the Delaunay triangulation allows to improve the results. All experiments are performed on a dataset of 2500 instances of 100 colour logo images in different rotations and scales. |
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Boston; USA; |
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978-1-60558-773-8 |
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DAG |
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DAG @ dag @ NKV2010 |
Serial |
1436 |
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Author |
Sebastien Mace; Herve Locteau; Ernest Valveny; Salvatore Tabbone |


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Title |
A system to detect rooms in architectural floor plan images |
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Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
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167–174 |
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In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical arrangements are combined into walls. We also present the way we detect some door hypothesis thanks to the extraction of arcs. Walls and door hypothesis are then used by our room segmentation strategy; it consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines between regions can also be rough. We take advantage of knowledge associated to architectural floor plans in order to obtain mostly rectangular rooms. Qualitative and quantitative evaluations performed on a corpus of real documents show promising results. |
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Boston; USA |
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978-1-60558-773-8 |
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DAG |
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no |
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DAG @ dag @ MLV2010 |
Serial |
1437 |
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Author |
Marçal Rusiñol; Josep Llados |

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Title |
Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections |
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Book Whole |
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Year |
2010 |
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Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections |
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Focused Retrieval , Graphical Pattern Indexation,Graphics Recognition ,Pattern Recognition , Performance Evaluation , Symbol Description ,Symbol Spotting |
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Abstract |
The specific problem of symbol recognition in graphical documents requires additional techniques to those developed for character recognition. The most well-known obstacle is the so-called Sayre paradox: Correct recognition requires good segmentation, yet improvement in segmentation is achieved using information provided by the recognition process. This dilemma can be avoided by techniques that identify sets of regions containing useful information. Such symbol-spotting methods allow the detection of symbols in maps or technical drawings without having to fully segment or fully recognize the entire content.
This unique text/reference provides a complete, integrated and large-scale solution to the challenge of designing a robust symbol-spotting method for collections of graphic-rich documents. The book examines a number of features and descriptors, from basic photometric descriptors commonly used in computer vision techniques to those specific to graphical shapes, presenting a methodology which can be used in a wide variety of applications. Additionally, readers are supplied with an insight into the problem of performance evaluation of spotting methods. Some very basic knowledge of pattern recognition, document image analysis and graphics recognition is assumed. |
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Springer |
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978-1-84996-208-7 |
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DAG |
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no |
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Call Number |
DAG @ dag @ RuL2010a |
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1292 |
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Author |
Alicia Fornes; Bart Lamiroy |


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Title |
Graphics Recognition, Current Trends and Evolutions |
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Book Whole |
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Year |
2018 |
Publication |
Graphics Recognition, Current Trends and Evolutions |
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Volume |
11009 |
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This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps. |
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Springer International Publishing |
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LNCS |
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978-3-030-02283-9 |
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DAG; 600.121 |
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no |
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Call Number |
Admin @ si @ FoL2018 |
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3171 |
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Author |
Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes |


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Title |
Optical Music Recognition by Long Short-Term Memory Networks |
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Book Chapter |
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Year |
2018 |
Publication |
Graphics Recognition. Current Trends and Evolutions |
Abbreviated Journal |
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Volume |
11009 |
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Pages |
81-95 |
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Keywords |
Optical Music Recognition; Recurrent Neural Network; Long ShortTerm Memory |
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Abstract |
Optical Music Recognition refers to the task of transcribing the image of a music score into a machine-readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level. The experimental results are promising, showing the benefits of our approach. |
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Springer |
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A. Fornes, B. Lamiroy |
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LNCS |
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ISBN  |
978-3-030-02283-9 |
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GREC |
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Notes |
DAG; 600.097; 601.302; 601.330; 600.121 |
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no |
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Call Number |
Admin @ si @ BRC2018 |
Serial |
3227 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |


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Title |
16th International Conference, 2021, Proceedings, Part II |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
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12822 |
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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Editor |
Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86330-2 |
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ICDAR |
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DAG |
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no |
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Call Number |
Admin @ si @ |
Serial |
3726 |
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Permanent link to this record |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |


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Title |
16th International Conference, 2021, Proceedings, Part III |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
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12823 |
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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86333-3 |
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ICDAR |
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DAG |
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no |
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Admin @ si @ |
Serial |
3727 |
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Permanent link to this record |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |


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Title |
16th International Conference, 2021, Proceedings, Part IV |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
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12824 |
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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86336-4 |
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ICDAR |
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DAG |
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no |
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Call Number |
Admin @ si @ |
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3728 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |


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Title |
16th International Conference, 2021, Proceedings, Part I |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
Abbreviated Journal |
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12821 |
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Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: historical document analysis, document analysis systems, handwriting recognition, scene text detection and recognition, document image processing, natural language processing (NLP) for document understanding, and graphics, diagram and math recognition. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Editor |
Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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ISBN  |
978-3-030-86548-1 |
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ICDAR |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ |
Serial |
3725 |
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Permanent link to this record |
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Author |
Sergi Garcia Bordils; George Tom; Sangeeth Reddy; Minesh Mathew; Marçal Rusiñol; C.V. Jawahar; Dimosthenis Karatzas |



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Title |
Read While You Drive-Multilingual Text Tracking on the Road |
Type |
Conference Article |
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Year |
2022 |
Publication |
15th IAPR International workshop on document analysis systems |
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13237 |
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Pages |
756–770 |
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Abstract |
Visual data obtained during driving scenarios usually contain large amounts of text that conveys semantic information necessary to analyse the urban environment and is integral to the traffic control plan. Yet, research on autonomous driving or driver assistance systems typically ignores this information. To advance research in this direction, we present RoadText-3K, a large driving video dataset with fully annotated text. RoadText-3K is three times bigger than its predecessor and contains data from varied geographical locations, unconstrained driving conditions and multiple languages and scripts. We offer a comprehensive analysis of tracking by detection and detection by tracking methods exploring the limits of state-of-the-art text detection. Finally, we propose a new end-to-end trainable tracking model that yields state-of-the-art results on this challenging dataset. Our experiments demonstrate the complexity and variability of RoadText-3K and establish a new, realistic benchmark for scene text tracking in the wild. |
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La Rochelle; France; May 2022 |
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LNCS |
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978-3-031-06554-5 |
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DAS |
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Notes |
DAG; 600.155; 611.022; 611.004 |
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no |
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Call Number |
Admin @ si @ GTR2022 |
Serial |
3783 |
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Permanent link to this record |