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Author |
D. Rincon; E. Frumento; M. Angel Viñas |
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Description of a teleconsultation platform and its interaction with access networks. |
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Conference Article |
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1999 |
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V Open European Summer School. 145–150. |
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Barcelona |
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ISE @ ise @ RFV1999 |
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32 |
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Author |
A. Auge; Javier Varona; Juan J. Villanueva |
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Title |
Tumour Segmentation in Mammographies with Neural Networks. Application to Tumoural Volume Approximation. |
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Conference Article |
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1997 |
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Proceedings of the VII NSPRIA, Vol. II, CVC–UAB |
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ISE @ ise @ AVV1997 |
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208 |
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Author |
David Rotger; Misael Rosales; Jaume Garcia; Oriol Pujol ; J. Mauri; Petia Radeva |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Active Vessel: A New Multimedia Workstation for Intravascular Ultrasound and Angiography Fusion |
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Journal Article |
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2003 |
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Computers in Cardiology |
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30 |
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65-68 |
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AcriveVessel is a new multimedia workstation which enables the visualization, acquisition and handling of both image modalities, on- and ofline. It enables DICOM v3.0 decompression and browsing, video acquisition,repmduction and storage for IntraVascular UltraSound (IVUS) and angiograms with their corresponding ECG,automatic catheter segmentation in angiography images (using fast marching algorithm). BSpline models definition for vessel layers on IVUS images sequence and an extensively validated tool to fuse information. This approach defines the correspondence of every IVUS image with its correspondent point in the angiogram and viceversa. The 3 0 reconstruction of the NUS catheterhessel enables real distance measurements as well as threedimensional visualization showing vessel tortuosity in the space. |
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IAM;MILAB;HuPBA |
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IAM @ iam @ RRG2003 |
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1647 |
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Author |
Josep Llados; Ernest Valveny; Enric Marti |
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Title |
Symbol Recognition in Document Image Analysis: Methods and Challenges |
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Book Chapter |
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2000 |
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Recent Research Developments in Pattern Recognition, Transworld Research Network, |
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1 |
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151–178. |
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81-86846-61-1 |
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DAG;IAM |
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IAM @ iam @ LVM2000 |
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1575 |
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Author |
Josep Llados; Enric Marti; Juan J.Villanueva |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Symbol recognition by error-tolerant subgraph matching between region adjacency graphs |
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Journal Article |
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2001 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence |
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23 |
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10 |
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1137-1143 |
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The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
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IAM @ iam @ LMV2001 |
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1581 |
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Author |
Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; I. Bardaji; Horst Bunke |
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Title |
A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach |
Type |
Journal Article |
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2011 |
Publication |
Computer Vision and Image Understanding |
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CVIU |
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115 |
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7 |
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919-928 |
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Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition |
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The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods. |
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DAG |
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IAM @ iam @ FKV2011 |
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1831 |
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Author |
Fernando Vilariño; Stephan Ameling; Gerard Lacey; Stephen Patchett; Hugh Mulcahy |
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Title |
Eye Tracking Search Patterns in Expert and Trainee Colonoscopists: A Novel Method of Assessing Endoscopic Competency? |
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Journal Article |
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2009 |
Publication |
Gastrointestinal Endoscopy |
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GI |
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69 |
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5 |
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370 |
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800 |
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MV;SIAI |
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fernando @ fernando @ |
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2420 |
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Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño |
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Title |
Texture-based Polyp Detection in Colonoscopy |
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Conference Article |
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2009 |
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Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN |
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800 |
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MV;SIAI |
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fernando @ fernando @ |
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2428 |
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Author |
C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
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Title |
Towards a general model of colour categorization which considers context |
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Journal Article |
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2010 |
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Perception. ECVP Abstract Supplement |
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PER |
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39 |
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86 |
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In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly dierent(more diuse) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we
completed our parametric fuzzy-sets model of colour naming space. |
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CIC |
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no |
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CAT @ cat @ PBV2010b |
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1326 |
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Author |
Maria Vanrell; Jordi Vitria; Xavier Roca |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
A multidimensional scaling approach to explore the behavior of a texture perception algorithm. |
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Journal Article |
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1997 |
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Machine Vision and Applications |
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9 |
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262–271 |
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OR;ISE;CIC;MV |
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BCNPCL @ bcnpcl @ VVR1997 |
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35 |
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Jordi Vitria; Petia Radeva; X. Binefa |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
EigenHistograms: using low dimensional models of color distribution for real time object recognition |
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Conference Article |
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1999 |
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Computer Analysis of Images and Patterns |
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Ljubliana, Slovenia, Springer-Verlag |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ VRB1999a |
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29 |
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F. Moreso; D. Seron; Jordi Vitria; J.M. Grinyo; F.M. Colome-Serra; N. Pares; J.R. Serra |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Quantification of Interstitial Chronic Renal Damage by means of Texture Analysis. |
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1994 |
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Kidney International |
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46 |
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6 |
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1721-1727 |
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BCNPCL @ bcnpcl @ MSV1994 |
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M. Bressan; Jordi Vitria |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Independent Component Analysis and Naïve Bayes Classification. |
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2002 |
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Proceedings of the Second IASTED International Conference Visualilzation, Imaging and Image Proceesing VIIP 2002: 496–501. |
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BCNPCL @ bcnpcl @ BrV2002a |
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288 |
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Javad Zolfaghari Bengar; Joost Van de Weijer; Bartlomiej Twardowski; Bogdan Raducanu |
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Title |
Reducing Label Effort: Self- Supervised Meets Active Learning |
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Conference Article |
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2021 |
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International Conference on Computer Vision Workshops |
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1631-1639 |
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Active learning is a paradigm aimed at reducing the annotation effort by training the model on actively selected informative and/or representative samples. Another paradigm to reduce the annotation effort is self-training that learns from a large amount of unlabeled data in an unsupervised way and fine-tunes on few labeled samples. Recent developments in self-training have achieved very impressive results rivaling supervised learning on some datasets. The current work focuses on whether the two paradigms can benefit from each other. We studied object recognition datasets including CIFAR10, CIFAR100 and Tiny ImageNet with several labeling budgets for the evaluations. Our experiments reveal that self-training is remarkably more efficient than active learning at reducing the labeling effort, that for a low labeling budget, active learning offers no benefit to self-training, and finally that the combination of active learning and self-training is fruitful when the labeling budget is high. The performance gap between active learning trained either with self-training or from scratch diminishes as we approach to the point where almost half of the dataset is labeled. |
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October 2021 |
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ICCVW |
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LAMP; |
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Admin @ si @ ZVT2021 |
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Author |
Javad Zolfaghari Bengar; Bogdan Raducanu; Joost Van de Weijer |
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Title |
When Deep Learners Change Their Mind: Learning Dynamics for Active Learning |
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Conference Article |
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2021 |
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19th International Conference on Computer Analysis of Images and Patterns |
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13052 |
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1 |
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403-413 |
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Abstract |
Active learning aims to select samples to be annotated that yield the largest performance improvement for the learning algorithm. Many methods approach this problem by measuring the informativeness of samples and do this based on the certainty of the network predictions for samples. However, it is well-known that neural networks are overly confident about their prediction and are therefore an untrustworthy source to assess sample informativeness. In this paper, we propose a new informativeness-based active learning method. Our measure is derived from the learning dynamics of a neural network. More precisely we track the label assignment of the unlabeled data pool during the training of the algorithm. We capture the learning dynamics with a metric called label-dispersion, which is low when the network consistently assigns the same label to the sample during the training of the network and high when the assigned label changes frequently. We show that label-dispersion is a promising predictor of the uncertainty of the network, and show on two benchmark datasets that an active learning algorithm based on label-dispersion obtains excellent results. |
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September 2021 |
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LAMP; |
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Serial |
3673 |
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