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Essex at ImageCLEFcaption 2020 task

García Seco de Herrera, Alba and Parrilla Andrade, Francisco and Bentley, Luke and Aceves Compean, Arely (2020) Essex at ImageCLEFcaption 2020 task. In: ImageClef 2020, ? - ?.

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Abstract

The University of Essex participated in the fourth edition of the ImageCLEFcaption task which aims to detect concepts on radiology images as an approach to medical image understanding. In this paper, the University of Essex team presents its participation in the ImageCLEF 2020 caption task based on a retrieval based approach for concept detection. A Densely Connected Convolutional Network is used to encode the images. This paper explores compares several modification of the baseline considering several aspects such as the image modality or the selection of concepts among the top retrieved images. The University of Essex was third best team participating in the task achieving a 0.381 mean F1 score, very close to the results obtained by the top two teams. Code and pre-trained models are available at https://github.com/fjpa121197/ImageCLEFmedEssex2020.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: CLEF2020 Working Notes
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 27 Sep 2022 12:02
Last Modified: 27 Sep 2022 12:02
URI: http://repository.essex.ac.uk/id/eprint/28665

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