Recent trends in emotion analysis: A big data analysis perspective
| dc.authorid | 0000-0001-6657-9738 | |
| dc.contributor.author | Özyer, Tansel | |
| dc.contributor.author | Ak, Duygu Selin | |
| dc.contributor.author | Alhajj, Reda | |
| dc.date.accessioned | 2021-08-26T06:39:33Z | |
| dc.date.available | 2021-08-26T06:39:33Z | |
| dc.date.issued | 2020 | |
| dc.department | İstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü | |
| dc.description.abstract | Human 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. | |
| dc.description.sponsorship | IEEE; Association for Computing Machinery; IEEE Computer Society; ACM SIGKDD; IEEE TCDE; Springer; Elsevier | en_US |
| dc.identifier.citation | Özyer, T., Ak, D. S. ve Alhajj, R. (2020). Recent trends in emotion analysis: A big data analysis perspective. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) içinde (710-714. ss.). 07-10 December 2020. https://dx.doi.org/10.1109/ASONAM49781.2020.9381441 | |
| dc.identifier.doi | 10.1109/ASONAM49781.2020.9381441 | |
| dc.identifier.endpage | 714 | |
| dc.identifier.isbn | 9781728110561 | |
| dc.identifier.issn | 2473-9928 | |
| dc.identifier.issn | 2473-991X | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 710 | |
| dc.identifier.uri | https://dx.doi.org/10.1109/ASONAM49781.2020.9381441 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12511/7983 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | IEEE-Institute of Electrical and Electronics Engineers | |
| dc.relation.ispartof | IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/embargoedAccess | |
| dc.subject | Human Activity Recognition | |
| dc.subject | Video Based Recognition | |
| dc.subject | Skeleton Based Recognition | |
| dc.title | Recent trends in emotion analysis: A big data analysis perspective | |
| dc.type | Conference Object |
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