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Author |
Ramon Baldrich |
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Title |
Perceptual approach to a computational colour-texture representation for surface inspection. |
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2001 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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CIC |
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no |
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Call Number |
CAT @ cat @ Bal2001 |
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73 |
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Author |
Ricardo Toledo |
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Title |
Cardiac workstation and dynamic model to assist in coronary tree analysis. |
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2001 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ph.D. thesis |
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Petia Radeva;JuanJose Villanueva |
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ADAS |
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no |
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Admin @ si @ Tol2001 |
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166 |
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Author |
Antonio Lopez |
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Title |
Multilocal Methods for Ridge and Valley Delineation in Image Analysis. |
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2000 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ph.D. thesis |
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Editor |
Joan Serrat |
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no |
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ADAS @ adas @ Lop2000 |
Serial |
174 |
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Author |
Felipe Lumbreras |
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Title |
Segmentation, classification and modelization of textures by means of multiresolution decomposition techniques. |
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Year |
2001 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ Lum2001 |
Serial |
188 |
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Author |
A. Pujol |
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Title |
Contributions to shape and texture face similarity measurement. |
Type |
Book Whole |
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Year |
2001 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Thesis |
Ph.D. thesis |
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Editor |
JuanJose Villanueva |
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no |
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Admin @ si @ Puj2001 |
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202 |
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Author |
David Lloret |
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Title |
Medical Image Registration Based on a Creaseress Measure. |
Type |
Book Whole |
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Year |
2002 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Thesis |
Ph.D. thesis |
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Editor |
Joan Serrat |
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no |
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Call Number |
Admin @ si @ Llo2002 |
Serial |
321 |
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Author |
Jordi Gonzalez |
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Title |
Human Sequence Evaluation: the Key-frame Approach |
Type |
Book Whole |
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Year |
2004 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Thesis |
Ph.D. thesis |
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Editor |
Xavier Roca;Javier Varona |
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Approved |
no |
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Call Number |
ISE @ ise @ Gon2004 |
Serial |
362 |
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Author |
David Guillamet |
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Title |
Statistical Local Appearance Models for Object Recognition |
Type |
Book Whole |
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Year |
2004 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Address |
Bellaterra |
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Thesis |
Ph.D. thesis |
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Editor |
Jordi Vitria |
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Approved |
no |
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Call Number |
Admin @ si @ Gui2004 |
Serial |
444 |
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Author |
Oriol Pujol |
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Title |
A semi-Supervised Statistical Framework and Generative Snakes for IVUS Analysis |
Type |
Book Whole |
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Year |
2004 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Address |
CVC (UAB), Bellaterra |
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Thesis |
Ph.D. thesis |
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Place of Publication |
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Editor |
Petia Radeva |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ Puj2004 |
Serial |
512 |
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Author |
David Masip |
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Title |
Face Classification Using Discriminative Features and Classifier Combination |
Type |
Book Whole |
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Year |
2005 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Address |
CVC (UAB) |
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Thesis |
Ph.D. thesis |
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Editor |
Jordi Vitria |
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ISBN |
84-933652-3-8 |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ Mas2005b |
Serial |
602 |
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Author |
Misael Rosales |
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Title |
A Physics-Based Image Modelling of IVUS as a Geometric and Kinematic System |
Type |
Book Whole |
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Year |
2005 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Address |
CVC (UAB) |
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Thesis |
Ph.D. thesis |
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Place of Publication |
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Editor |
Petia Radeva |
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Expedition |
978-84-922529-8-7 |
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Notes |
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Approved |
no |
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Call Number |
Admin @ si @ Ros2005 |
Serial |
603 |
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Author |
Fernando Vilariño |
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Title |
A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy |
Type |
Book Whole |
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Year |
2006 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Abstract |
Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions obtained by labelling all the motility events present in a video provided by a capsule with a wireless micro-camera, which is ingested by the patient. However, the visual analysis of these video sequences presents several im- portant drawbacks, mainly related to both the large amount of time needed for the visualization process, and the low prevalence of intestinal contractions in video.
In this work we propose a machine learning system to automatically detect the intestinal contractions in video capsule endoscopy, driving a very useful but not fea- sible clinical routine into a feasible clinical procedure. Our proposal is divided into two different parts: The first part tackles the problem of the automatic detection of phasic contractions in capsule endoscopy videos. Phasic contractions are dynamic events spanning about 4-5 seconds, which show visual patterns with a high variability. Our proposal is based on a sequential design which involves the analysis of textural, color and blob features with powerful classifiers such as SVM. This approach appears to cope with two basic aims: the reduction of the imbalance rate of the data set, and the modular construction of the system, which adds the capability of including domain knowledge as new stages in the cascade. The second part of the current work tackles the problem of the automatic detection of tonic contractions. Tonic contrac- tions manifest in capsule endoscopy as a sustained pattern of the folds and wrinkles of the intestine, which may be prolonged for an undetermined span of time. Our proposal is based on the analysis of the wrinkle patterns, presenting a comparative study of diverse features and classification methods, and providing a set of appro- priate descriptors for their characterization. We provide a detailed analysis of the performance achieved by our system both in a qualitative and a quantitative way. |
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Address |
CVC (UAB) |
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Thesis |
Ph.D. thesis |
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Publisher |
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Editor |
Petia Radeva |
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Original Title |
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Series Title |
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Series Issue |
84-933652-7-0 |
Edition |
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ISSN |
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Area |
800 |
Expedition |
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Conference |
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Notes |
MV;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ Vil2006; IAM @ iam @ Vil2006 |
Serial |
738 |
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Author |
Aymen Azaza |
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Title |
Context, Motion and Semantic Information for Computational Saliency |
Type |
Book Whole |
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Year |
2018 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Abstract |
The main objective of this thesis is to highlight the salient object in an image or in a video sequence. We address three important—but in our opinion
insufficiently investigated—aspects of saliency detection. Firstly, we start
by extending previous research on saliency which explicitly models the information provided from the context. Then, we show the importance of
explicit context modelling for saliency estimation. Several important works
in saliency are based on the usage of object proposals. However, these methods
focus on the saliency of the object proposal itself and ignore the context.
To introduce context in such saliency approaches, we couple every object
proposal with its direct context. This allows us to evaluate the importance
of the immediate surround (context) for its saliency. We propose several
saliency features which are computed from the context proposals including
features based on omni-directional and horizontal context continuity. Secondly,
we investigate the usage of top-downmethods (high-level semantic
information) for the task of saliency prediction since most computational
methods are bottom-up or only include few semantic classes. We propose
to consider a wider group of object classes. These objects represent important
semantic information which we will exploit in our saliency prediction
approach. Thirdly, we develop a method to detect video saliency by computing
saliency from supervoxels and optical flow. In addition, we apply the
context features developed in this thesis for video saliency detection. The
method combines shape and motion features with our proposed context
features. To summarize, we prove that extending object proposals with their
direct context improves the task of saliency detection in both image and
video data. Also the importance of the semantic information in saliency
estimation is evaluated. Finally, we propose a newmotion feature to detect
saliency in video data. The three proposed novelties are evaluated on standard
saliency benchmark datasets and are shown to improve with respect to
state-of-the-art. |
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Address |
October 2018 |
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Corporate Author |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Joost Van de Weijer;Ali Douik |
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Language |
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ISBN |
978-84-945373-9-4 |
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Notes |
LAMP; 600.120 |
Approved |
no |
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Call Number |
Admin @ si @ Aza2018 |
Serial |
3218 |
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| Permanent link to this record |
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Author |
Miquel Ferrer |
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Title |
Theory and Algorithms on the Median Graph. Application to Graph-based Classification and Clustering |
Type |
Book Whole |
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Year |
2008 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Thesis |
Ph.D. thesis |
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Editor |
Francesc Serratosa Casanelles;Ernest Valveny |
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Expedition |
978-84-935251-7-0 |
Conference |
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Notes |
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Approved |
no |
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Call Number |
Admin @ si @ Fer2008 |
Serial |
1105 |
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| Permanent link to this record |
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Author |
Daniel Ponsa |
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Title |
Model-Based Visual Localisation of Contours and Vehicles |
Type |
Book Whole |
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Year |
2007 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Volume |
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Pages |
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Keywords |
Phd Thesis |
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Abstract |
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Address |
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Corporate Author |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Antonio Lopez;Xavier Roca |
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Language |
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Summary Language |
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Series Editor |
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Series Issue |
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Edition |
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ISBN |
978-84-935251-3-2 |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ Pon2007 |
Serial |
1107 |
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| Permanent link to this record |
