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        <title>A Survey on Biomedical Image Captioning</title>
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    <abstract>Image captioning applied to biomedical images can assist and accelerate the diagnosis process followed by clinicians. This article is the first survey of biomedical image captioning, discussing datasets, evaluation measures, and state of the art methods. Additionally, we suggest two baselines, a weak and a stronger one; the latter outperforms all current state of the art systems on one of the datasets.</abstract>
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    <identifier type="doi">10.18653/v1/W19-1803</identifier>
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%0 Conference Proceedings
%T A Survey on Biomedical Image Captioning
%A Pavlopoulos, John
%A Kougia, Vasiliki
%A Androutsopoulos, Ion
%S Proceedings of the Second Workshop on Shortcomings in Vision and Language
%D 2019
%8 jun
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F pavlopoulos-etal-2019-survey
%X Image captioning applied to biomedical images can assist and accelerate the diagnosis process followed by clinicians. This article is the first survey of biomedical image captioning, discussing datasets, evaluation measures, and state of the art methods. Additionally, we suggest two baselines, a weak and a stronger one; the latter outperforms all current state of the art systems on one of the datasets.
%R 10.18653/v1/W19-1803
%U https://aclanthology.org/W19-1803
%U https://doi.org/10.18653/v1/W19-1803
%P 26-36

Markdown (Informal)

[A Survey on Biomedical Image Captioning](https://aclanthology.org/W19-1803) (Pavlopoulos et al., 2019)

• A Survey on Biomedical Image Captioning (Pavlopoulos et al., 2019)

ACL

• John Pavlopoulos, Vasiliki Kougia, and Ion Androutsopoulos. 2019. A Survey on Biomedical Image Captioning. In Proceedings of the Second Workshop on Shortcomings in Vision and Language, pages 26–36, Minneapolis, Minnesota. Association for Computational Linguistics.