Deep Learning for Automatic Image Captioning in Poor Training Conditions

Recent advancements in Deep Learning have proved that an architecture that combines Convolutional Neural Networks and Recurrent Neural Networks enables the definition of very effective methods for the automatic captioning of images. The disadvantage that comes with this straightforward result is tha...

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Autores principales:	Caterina Masotti, Danilo Croce, Roberto Basili
Formato:	article
Lenguaje:	EN
Publicado:	Accademia University Press 2018
Materias:	Social Sciences H Computational linguistics. Natural language processing P98-98.5
Acceso en línea:	https://doaj.org/article/d188409df73f4a0b9ca8455085902f24
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spelling	oai:doaj.org-article:d188409df73f4a0b9ca8455085902f242021-12-02T09:52:21ZDeep Learning for Automatic Image Captioning in Poor Training Conditions2499-455310.4000/ijcol.538https://doaj.org/article/d188409df73f4a0b9ca8455085902f242018-06-01T00:00:00Zhttp://journals.openedition.org/ijcol/538https://doaj.org/toc/2499-4553Recent advancements in Deep Learning have proved that an architecture that combines Convolutional Neural Networks and Recurrent Neural Networks enables the definition of very effective methods for the automatic captioning of images. The disadvantage that comes with this straightforward result is that this approach requires the existence of large-scale corpora, which are not available for many languages.This paper introduces a simple methodology to automatically acquire a large-scale corpus of 600 thousand image/sentences pairs in Italian. At the best of our knowledge, this corpus has been used to train one of the first neural captioning systems for the same language. The experimental evaluation over a subset of validated image/captions pairs suggests that the achieved results are comparable with the English counterpart, despite a reduced amount of training examples.Caterina MasottiDanilo CroceRoberto BasiliAccademia University PressarticleSocial SciencesHComputational linguistics. Natural language processingP98-98.5ENIJCoL, Vol 4, Iss 1, Pp 43-55 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Social Sciences H Computational linguistics. Natural language processing P98-98.5
spellingShingle	Social Sciences H Computational linguistics. Natural language processing P98-98.5 Caterina Masotti Danilo Croce Roberto Basili Deep Learning for Automatic Image Captioning in Poor Training Conditions
description	Recent advancements in Deep Learning have proved that an architecture that combines Convolutional Neural Networks and Recurrent Neural Networks enables the definition of very effective methods for the automatic captioning of images. The disadvantage that comes with this straightforward result is that this approach requires the existence of large-scale corpora, which are not available for many languages.This paper introduces a simple methodology to automatically acquire a large-scale corpus of 600 thousand image/sentences pairs in Italian. At the best of our knowledge, this corpus has been used to train one of the first neural captioning systems for the same language. The experimental evaluation over a subset of validated image/captions pairs suggests that the achieved results are comparable with the English counterpart, despite a reduced amount of training examples.
format	article
author	Caterina Masotti Danilo Croce Roberto Basili
author_facet	Caterina Masotti Danilo Croce Roberto Basili
author_sort	Caterina Masotti
title	Deep Learning for Automatic Image Captioning in Poor Training Conditions
title_short	Deep Learning for Automatic Image Captioning in Poor Training Conditions
title_full	Deep Learning for Automatic Image Captioning in Poor Training Conditions
title_fullStr	Deep Learning for Automatic Image Captioning in Poor Training Conditions
title_full_unstemmed	Deep Learning for Automatic Image Captioning in Poor Training Conditions
title_sort	deep learning for automatic image captioning in poor training conditions
publisher	Accademia University Press
publishDate	2018
url	https://doaj.org/article/d188409df73f4a0b9ca8455085902f24
work_keys_str_mv	AT caterinamasotti deeplearningforautomaticimagecaptioninginpoortrainingconditions AT danilocroce deeplearningforautomaticimagecaptioninginpoortrainingconditions AT robertobasili deeplearningforautomaticimagecaptioninginpoortrainingconditions
_version_	1718397970947244032

Deep Learning for Automatic Image Captioning in Poor Training Conditions

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