Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5914
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dc.contributor.authorOzyer T.-
dc.contributor.authorSelin A.D.-
dc.contributor.authorAlhajj R.-
dc.date.accessioned2021-09-11T15:20:45Z-
dc.date.available2021-09-11T15:20:45Z-
dc.date.issued2020en_US
dc.identifier.citation12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020, 7 December 2020 through 10 December 2020, , 168050en_US
dc.identifier.isbn9781728110561-
dc.identifier.urihttps://doi.org/10.1109/ASONAM49781.2020.9381441-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5914-
dc.description.abstractHuman action recognition has recently started to find its way into applications in different applications. Accordingly, human action recognition methods are becoming increasingly important in our daily life. They are used for different purposes such as automation, security, surveillance, health, smart home systems, and customer behaviour prediction, among others. Though have more systems with methods provides a rich pool of choices, it is important to well understand the performance of these systems and their success rates in recognizing the right activities in order to decide on the most appropriate system for the current application domain. This survey tackles this issue by analyzing and commenting on the available human action recognition systems and methods. © 2020 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHuman activity recognitionen_US
dc.subjectskeleton based recognitionen_US
dc.subjectvideo based recognitionen_US
dc.titleRecent Trends in Emotion Analysis: a Big Data Analysis Perspectiveen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.startpage710en_US
dc.identifier.endpage714en_US
dc.identifier.wosWOS:000678816900112en_US
dc.identifier.scopus2-s2.0-85103696323en_US
dc.institutionauthorÖzyer, Tansel-
dc.identifier.doi10.1109/ASONAM49781.2020.9381441-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020en_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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