IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things

IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things

Big data processing includes both data management and data analytics. The data management step requires efficient cleaning, knowledge extraction, and integration and aggregation methods, whereas Internet-of-Multimedia-Things (IoMT) analysis is based on knowledge modeling and interpretation, which is...

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Main Authors: Zhihan Lv, Irfan Mehmood, Mario Vento, Minh-Son Dao, Kaoru Ota, Alessia Saggese
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Online Access:https://ieeexplore.ieee.org/document/8727546/
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spelling doaj-0ebf1dcfaa5f4394b79b9ee642b403982021-03-30T00:14:32ZengIEEEIEEE Access2169-35362019-01-017652116521810.1109/ACCESS.2019.29154878727546IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-ThingsZhihan Lv0Irfan Mehmood1Mario Vento2Minh-Son Dao3Kaoru Ota4Alessia Saggese5Qingdao University, Qingdao, ChinaSejong University, Seoul, South KoreaUniversity of Salerno, Fisciano, ItalyBig Data Analytics Laboratory, National Institute of Information and Communications Technology (NICT), Tokyo, JapanMuroran Institute of Technology, Muroran, JapanUniversity of Salerno, Fisciano, ItalyBig data processing includes both data management and data analytics. The data management step requires efficient cleaning, knowledge extraction, and integration and aggregation methods, whereas Internet-of-Multimedia-Things (IoMT) analysis is based on knowledge modeling and interpretation, which is more often performed by exploiting deep learning architectures. In the past couple of years, merging conventional and deep learning methodologies has exhibited great promise in ingesting multimedia big data, exploring the paradigm of transfer learning, association rule mining, and predictive analytics etc.https://ieeexplore.ieee.org/document/8727546/
collection DOAJ
language English
format Article
sources DOAJ
author Zhihan Lv
Irfan Mehmood
Mario Vento
Minh-Son Dao
Kaoru Ota
Alessia Saggese
spellingShingle Zhihan Lv
Irfan Mehmood
Mario Vento
Minh-Son Dao
Kaoru Ota
Alessia Saggese
IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things
IEEE Access
author_facet Zhihan Lv
Irfan Mehmood
Mario Vento
Minh-Son Dao
Kaoru Ota
Alessia Saggese
author_sort Zhihan Lv
title IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things
title_short IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things
title_full IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things
title_fullStr IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things
title_full_unstemmed IEEE Access Special Section Editorial: Multimedia Analysis for Internet-of-Things
title_sort ieee access special section editorial: multimedia analysis for internet-of-things
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description Big data processing includes both data management and data analytics. The data management step requires efficient cleaning, knowledge extraction, and integration and aggregation methods, whereas Internet-of-Multimedia-Things (IoMT) analysis is based on knowledge modeling and interpretation, which is more often performed by exploiting deep learning architectures. In the past couple of years, merging conventional and deep learning methodologies has exhibited great promise in ingesting multimedia big data, exploring the paradigm of transfer learning, association rule mining, and predictive analytics etc.
url https://ieeexplore.ieee.org/document/8727546/
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AT minhsondao ieeeaccessspecialsectioneditorialmultimediaanalysisforinternetofthings
AT kaoruota ieeeaccessspecialsectioneditorialmultimediaanalysisforinternetofthings
AT alessiasaggese ieeeaccessspecialsectioneditorialmultimediaanalysisforinternetofthings
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