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Overview of the ImageCLEF 2016 Scalable Concept Image Annotation Task

Gilbert, Andrew, Piras, L, Wang, J, Yan, Fei, Ramisa, A, Dellandrea, E, Gaizauskas, R, Villegas, M and Mikolajczyk, Krystian (2016) Overview of the ImageCLEF 2016 Scalable Concept Image Annotation Task In: 7th International Conference of the CLEF Association, Clef 2016, 2016-09-05 - 2016-09-08, Portugal.

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Since 2010, ImageCLEF has run a scalable image annotation task, to promote research into the annotation of images using noisy web page data. It aims to develop techniques to allow computers to describe images reliably, localise di erent concepts depicted and generate descriptions of the scenes. The primary goal of the challenge is to encourage creative ideas of using web page data to improve image annotation. Three subtasks and two pilot teaser tasks were available to participants; all tasks use a single mixed modality data source of 510,123 web page items for both training and test. The dataset included raw images, textual features obtained from the web pages on which the images appeared, as well as extracted visual features. Extracted from the Web by querying popular image search engines, the dataset was formed. For the main subtasks, the development and test sets were both taken from the \training set". For the teaser tasks, 200,000 web page items were reserved for testing, and a separate development set was provided. The 251 concepts were chosen to be visual objects that are localizable and that are useful for generating textual descriptions of the visual content of images and were mined from the texts of our extensive database of image-webpage pairs. This year seven groups participated in the task, submitting over 50 runs across all subtasks, and all participants also provided working notes papers. In general, the groups' performance is impressive across the tasks, and there are interesting insights into these very relevant challenges.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Piras, L
Wang, J
Ramisa, A
Dellandrea, E
Gaizauskas, R
Villegas, M
Date : 23 August 2016
DOI : 10.1007/978-3-319-44564-9_25
Copyright Disclaimer : © Springer International Publishing Switzerland 2016
Uncontrolled Keywords : Mean Average Precision; Image Annotation; Biomedical Literature; Normalize Discount Cumulative Gain; Evaluation Campaign
Depositing User : Symplectic Elements
Date Deposited : 11 Oct 2016 14:46
Last Modified : 22 May 2019 16:23

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