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The Visual Concept Detection Task in ImageCLEF 2008 [chapter]

Thomas Deselaers, Allan Hanbury
2009 Lecture Notes in Computer Science  
The Visual Concept Detection Task (VCDT) of ImageCLEF 2008 is described. A database of 2,827 images were manually annotated with 17 concepts.  ...  Of these, 1,827 were used for training and 1,000 for testing the automated assignment of categories. In total 11 groups participated and submitted 53 runs.  ...  Conclusion This paper summarises the ImageCLEF 2008 Visual Concept Detection Task.  ... 
doi:10.1007/978-3-642-04447-2_65 fatcat:6x4tzrfb2vb3vcrdbdawok4yv4

Object and Concept Recognition for Image Retrieval [chapter]

Stefanie Nowak, Allan Hanbury, Thomas Deselaers
2010 ImageCLEF  
The visual object and concept detection task evolved over the years to become an inherent part of the yearly ImageCLEF evaluation cycle with growing interest and participation from the research community  ...  ImageCLEF introduced its first automatic annotation task for photos in 2006.  ...  Acknowledgements We would like to thank the organizers of CLEF and ImageCLEF for the support of the object and concept recognition tasks.  ... 
doi:10.1007/978-3-642-15181-1_11 fatcat:o762fbqycrg2lcvuimen2h2yoq

SZTAKI @ ImageCLEF 2008: Visual Feature Analysis in Segmented Images [chapter]

Bálint Daróczy, Zsolt Fekete, Mátyás Brendel, Simon Rácz, András Benczúr, Dávid Siklósi, Attila Pereszlényi
2009 Lecture Notes in Computer Science  
We describe our image processing system used in the Image-CLEF 2008 Photo Retrieval and Visual Concept Detection tasks.  ...  In the paper we elaborate on the importance of choices in the segmentation procedure with emphasis on edge detection.  ...  Conclusion and future work We have demonstrated that image segmentation based retrieval and categorization systems perform well and analyzed the right choice for the segmenter and the visual features.  ... 
doi:10.1007/978-3-642-04447-2_81 fatcat:kpvvx3iapvgszgmmdgyuupegs4

Feature Annotation for Visual Concept Detection in ImageCLEF 2008

Jingtian Jiang, Xiaoguang Rui, Nenghai Yu
2008 Conference and Labs of the Evaluation Forum  
This paper shows our work on CLEF 2008. Our group joined the Visual Concept Detection Task of ImageCLEF 2008 this year. We submitted one run (run id: HJ_FA) for the evaluation.  ...  In the run, we applied a method called "Feature Annotation" to detect visual concept for the predefined concepts and we want to know how this information help in solving the photographic retrieval task  ...  Acknowledgments The research is supported in part by National Natural Science Foundation of China (60672056) and USTC Postgraduate Innovation Foundation.  ... 
dblp:conf/clef/JiangRY08 fatcat:qqtbhv6z5fc37oepejo2wgirqa

The University of Amsterdam's Concept Detection System at ImageCLEF 2009 [chapter]

Koen E. A. van de Sande, Theo Gevers, Arnold W. M. Smeulders
2010 Lecture Notes in Computer Science  
Our group within the University of Amsterdam participated in the large-scale visual concept detection task of ImageCLEF 2009.  ...  The participation in ImageCLEF 2009 has been successful, resulting in the top ranking for the large-scale visual concept detection task in terms of both EER and AUC.  ...  Acknowledgements This work was supported by the EC-FP6 VIDI-Video project.  ... 
doi:10.1007/978-3-642-15751-6_32 fatcat:u567lmju65dw7pnchh4xaxbhya

SZTAKI @ ImageCLEF 2008: Visual Concept Detection

Bálint Daróczy, Zsolt Fekete, Mátyás Brendel
2008 Conference and Labs of the Evaluation Forum  
We describe our approach to the ImageCLEF-VisualConcept 2008 task.  ...  We are planning to provide improved analysis in the near future.  ...  The Visual Concept Detection Task has the objective to identify visual concepts.  ... 
dblp:conf/clef/DaroczyFB08 fatcat:f2lg6i7wxfe6zdarahkdcy43ra

ImageCLEF 2013: The Vision, the Data and the Open Challenges [chapter]

Barbara Caputo, Henning Muller, Bart Thomee, Mauricio Villegas, Roberto Paredes, David Zellhofer, Herve Goeau, Alexis Joly, Pierre Bonnet, Jesus Martinez Gomez, Ismael Garcia Varea, Miguel Cazorla
2013 Lecture Notes in Computer Science  
Furthermore, the medical annotation task, that traditionally has been under the ImageCLEF umbrella and that this year celebrates its tenth anniversary, has been organized in conjunction with AMIA for the  ...  Since its first edition in 2003, ImageCLEF has become one of the key initiatives promoting the benchmark evaluation of algorithms for the cross-language annotation and retrieval of images in various domains  ...  a realistic and challenging benchmark for visual concept detection, annotation and retrieval in the context of personal photo and web image collections.  ... 
doi:10.1007/978-3-642-40802-1_26 fatcat:wi5nqtvoxbch3jtl2u7qzwo5fm

Profil Entropic Visual Features for Visual Concept Detection in CLEF 2008 Campaign

Hervé Glotin, Zhongqiu Zhao
2008 Conference and Labs of the Evaluation Forum  
In this task, we used only visual information to implement the VCDT task. We defined and compared two simple projection operators : the harmonic and arithmetic means.  ...  These features, called Profil Entropy Features (PEF), were added to usual color means and variances, and then were fed to SVM classifiers for the detection of 17 visual concepts on the IARPR images during  ...  Acknowledgment This work was partially supported by the French National Agency of Research (ANR-06-MDCA-002).  ... 
dblp:conf/clef/GlotinZ08a fatcat:dgmxodfg7ren3c6jeec5p4s2ra

The Wikipedia Image Retrieval Task [chapter]

Theodora Tsikrika, Jana Kludas
2010 ImageCLEF  
This chapter presents an overview of the available test collections, summarises the retrieval approaches employed by the groups that participated in the task during the 2008 and 2009 ImageCLEF campaigns  ...  The Wikipedia image retrieval task at ImageCLEF provides a test-bed for the system-oriented evaluation of visual information retrieval from a collection of Wikipedia images.  ...  track, Thomas Deselaers for invaluable technical support during ImageCLEF 2008, and all the groups that participated in the task and in the relevance assessment process.  ... 
doi:10.1007/978-3-642-15181-1_9 fatcat:gn2lisoma5fhhhfaxqyxc55l6e

PKU at ImageCLEF 2008: Experiments with Query Extension Techniques for Text-Based and Content-Based Image Retrieval

Zhi Zhou, Yonghong Tian, Yuanning Li, Ting Liu, Tiejun Huang, Wen Gao
2008 Conference and Labs of the Evaluation Forum  
In this paper, we present our solutions for the WikipediaMM task at ImageCLEF 2008.  ...  search, and then treat the retrieval task as visual concept detection in the given Wikipedia image set. By comparison, this approach performs better than other submitted CBIR runs.  ...  Introduction ImageCLEF 2008 contains five different tasks (i.e., photo retrieval, medical retrieval, visual concept detection, medical annotation, and WikipediaMM).  ... 
dblp:conf/clef/ZhouTLLHG08 fatcat:qvoyliez4jb5zec5wq7qn5jchu

An Overview of Evaluation Campaigns in Multimedia Retrieval [chapter]

Suzanne Little, Ainhoa Llorente, Stefan Rüger
2010 ImageCLEF  
for starting ImageCLEF and then a summary of the tracks run over the seven years (data, tasks and participants).  ...  for evaluating visual information retrieval systems and is the focus of this book.  ...  In particular we thank the European Union for support through the funding of various EU projects that have supported task organisers.  ... 
doi:10.1007/978-3-642-15181-1_27 fatcat:nnglqvlfw5a6fceju5vrwyswim

Seven Years of Image Retrieval Evaluation [chapter]

Paul Clough, Henning Müller, Mark Sanderson
2010 ImageCLEF  
for starting ImageCLEF and then a summary of the tracks run over the seven years (data, tasks and participants).  ...  for evaluating visual information retrieval systems and is the focus of this book.  ...  In particular we thank the European Union for support through the funding of various EU projects that have supported task organisers.  ... 
doi:10.1007/978-3-642-15181-1_1 fatcat:yuvmyscbufg5lclr36z4pughm4

Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation [chapter]

Bogdan Ionescu, Henning Müller, Mauricio Villegas, Alba García Seco de Herrera, Carsten Eickhoff, Vincent Andrearczyk, Yashin Dicente Cid, Vitali Liauchuk, Vassili Kovalev, Sadid A. Hasan, Yuan Ling, Oladimeji Farri (+8 others)
2018 Lecture Notes in Computer Science  
In 2018, the 16th edition of ImageCLEF ran three main tasks and a pilot task: 1) a caption prediction task that aims at predicting the caption of a figure from the biomedical literature based only on the  ...  figure image; 2) a tuberculosis task that aims at detecting the tuberculosis type, severity and drug resistance from CT (Computed Tomography) volumes of the lung; 3) a LifeLog task (videos, images and  ...  The first task, concept detection, aims to extract the main biomedical concepts represented in an image based only on its visual content.  ... 
doi:10.1007/978-3-319-98932-7_28 fatcat:aehcejex5babrn4jpl6qsfdiye

Overview of the WikipediaMM Task at ImageCLEF 2008 [chapter]

Theodora Tsikrika, Jana Kludas
2009 Lecture Notes in Computer Science  
It became a part of the ImageCLEF evaluation campaign in 2008 with the aim of investigating the use of visual and textual sources in combination for improving the retrieval performance.  ...  The wikipediaMM task provides a testbed for the systemoriented evaluation of ad-hoc retrieval from a large collection of Wikipedia images.  ...  The authors would also like to thank Thomas Deselaers for invaluable technical support and all the groups participating in the relevance assessment process.  ... 
doi:10.1007/978-3-642-04447-2_66 fatcat:f6rigt25y5dynef6r3ffjxh3li

X-ray image categorization and retrieval using patch-based visualwords representation

Uri Avni, Hayit Greenspan, Michal Sharon, Eli Konen, Jacob Goldberger
2009 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
In a recent international competition the system was ranked as one of the top schemes in discriminating orientation and body regions in x-ray images, and in medical visual retrieval.  ...  On a set of 102 chest radiographs taken from routine hospital examination, the system detects pathology with sensitivity of 94% and specificity of 91%.  ...  Using the same methods, we have developed an image retrieval utility, which was ranked first in ImageClef 2008 among the visual retrieval systems.  ... 
doi:10.1109/isbi.2009.5193056 dblp:conf/isbi/AvniGSKG09 fatcat:uolonl2mhbcudb5xgzeqsyz67m
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