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dc.contributor.authorTanti, Marc-
dc.contributor.authorGatt, Albert-
dc.contributor.authorMuscat, Adrian-
dc.date.accessioned2022-12-21T10:03:25Z-
dc.date.available2022-12-21T10:03:25Z-
dc.date.issued2018-
dc.identifier.citationTanti, M., Gatt, A., & Muscat, A. (2018). Pre-gen metrics : predicting caption quality metrics without generating captions. In Computer Vision – ECCV 2018 Workshops (pp. 114-123). Manhattan: Springer International Publishing.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/104590-
dc.description.abstractImage caption generation systems are typically evaluated against reference outputs. We show that it is possible to predict output quality without generating the captions, based on the probability assigned by the neural model to the reference captions. Such pre-gen metrics are strongly correlated to standard evaluation metrics.en_GB
dc.language.isoenen_GB
dc.publisherSpringer International Publishingen_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectSubtitles (Motion pictures, television, etc.)en_GB
dc.subjectNeural networks (Computer science)en_GB
dc.subjectVersificationen_GB
dc.titlePre-gen metrics : predicting caption quality metrics without generating captionsen_GB
dc.title.alternativeComputer Vision – ECCV 2018 Workshopsen_GB
dc.typebookParten_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.description.reviewedpeer-revieweden_GB
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