Purify noisy data from annotated images using Montylingua and control redundant term

Dynamic growths in the field of digital data and new techniques (manual and automatic) are introduced to tag images. Tagging of an object within the image is labeled in different terms base on the user perception. LabelMe is the image datasets that give a user online access to labeled object through...

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Main Authors: Ullah, R., Jaafar, J., Said, A.B.M.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.26019 /
Published: Asian Research Publishing Network 2015
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953449990&partnerID=40&md5=e06e6d636e76c46df5854668626cbf32
http://eprints.utp.edu.my/26019/
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spelling utp-eprints.260192021-08-30T08:50:05Z Purify noisy data from annotated images using Montylingua and control redundant term Ullah, R. Jaafar, J. Said, A.B.M. Dynamic growths in the field of digital data and new techniques (manual and automatic) are introduced to tag images. Tagging of an object within the image is labeled in different terms base on the user perception. LabelMe is the image datasets that give a user online access to labeled object through by webtool. However, there are a number of noisy terms and errors found in the annotated list. Nevertheless, sometime a user tags the same objects with repeated terms. It requires to pruning the dataset from errors, noisy keywords and reduces to one instance term. This paper uses Montylingua for two purposes. First, it converts the tag term into base form. Second it purifies the irrelevant terms from the list. Next reduce the repeated terms into one instance and display their total count of occurrence. An experiment work, it shows that the purified list of the tagging has successfully removed from the annotated images. The result depicts through tagging ratio as well as degree of retrieval for effective achieved. Asian Research Publishing Network 2015 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953449990&partnerID=40&md5=e06e6d636e76c46df5854668626cbf32 Ullah, R. and Jaafar, J. and Said, A.B.M. (2015) Purify noisy data from annotated images using Montylingua and control redundant term. ARPN Journal of Engineering and Applied Sciences, 10 (23). pp. 18193-18199. http://eprints.utp.edu.my/26019/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Dynamic growths in the field of digital data and new techniques (manual and automatic) are introduced to tag images. Tagging of an object within the image is labeled in different terms base on the user perception. LabelMe is the image datasets that give a user online access to labeled object through by webtool. However, there are a number of noisy terms and errors found in the annotated list. Nevertheless, sometime a user tags the same objects with repeated terms. It requires to pruning the dataset from errors, noisy keywords and reduces to one instance term. This paper uses Montylingua for two purposes. First, it converts the tag term into base form. Second it purifies the irrelevant terms from the list. Next reduce the repeated terms into one instance and display their total count of occurrence. An experiment work, it shows that the purified list of the tagging has successfully removed from the annotated images. The result depicts through tagging ratio as well as degree of retrieval for effective achieved.
format Article
author Ullah, R.
Jaafar, J.
Said, A.B.M.
spellingShingle Ullah, R.
Jaafar, J.
Said, A.B.M.
Purify noisy data from annotated images using Montylingua and control redundant term
author_sort Ullah, R.
title Purify noisy data from annotated images using Montylingua and control redundant term
title_short Purify noisy data from annotated images using Montylingua and control redundant term
title_full Purify noisy data from annotated images using Montylingua and control redundant term
title_fullStr Purify noisy data from annotated images using Montylingua and control redundant term
title_full_unstemmed Purify noisy data from annotated images using Montylingua and control redundant term
title_sort purify noisy data from annotated images using montylingua and control redundant term
publisher Asian Research Publishing Network
publishDate 2015
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953449990&partnerID=40&md5=e06e6d636e76c46df5854668626cbf32
http://eprints.utp.edu.my/26019/
_version_ 1741197070333640704
score 11.62408

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