Real-time object entity detection system for smart surveillance application
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ko, K. E. | - |
dc.contributor.author | Sim, K. B. | - |
dc.date.available | 2019-03-08T07:57:21Z | - |
dc.date.issued | 2017-09 | - |
dc.identifier.issn | 0013-5194 | - |
dc.identifier.issn | 1350-911X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/3941 | - |
dc.description.abstract | A real-time scheme for detecting object entities in real-time among a set of objects contained in the same class category is proposed. Building a unified framework for real-time object entity detection system without an additional training process to distinguish the object entities while minimising the loss of accuracy is focused. The experimental results on a benchmark dataset demonstrate that the method shows outstanding precision performance while achieving state-of-the-art object detection speed. | - |
dc.format.extent | 3 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | INST ENGINEERING TECHNOLOGY-IET | - |
dc.title | Real-time object entity detection system for smart surveillance application | - |
dc.type | Article | - |
dc.identifier.doi | 10.1049/el.2017.1532 | - |
dc.identifier.bibliographicCitation | ELECTRONICS LETTERS, v.53, no.19, pp 1304 - 1306 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000411158800012 | - |
dc.identifier.scopusid | 2-s2.0-85029665531 | - |
dc.citation.endPage | 1306 | - |
dc.citation.number | 19 | - |
dc.citation.startPage | 1304 | - |
dc.citation.title | ELECTRONICS LETTERS | - |
dc.citation.volume | 53 | - |
dc.type.docType | Article | - |
dc.publisher.location | 영국 | - |
dc.subject.keywordAuthor | object detection | - |
dc.subject.keywordAuthor | surveillance | - |
dc.subject.keywordAuthor | real-time object entity detection system | - |
dc.subject.keywordAuthor | smart surveillance application | - |
dc.subject.keywordAuthor | unified framework | - |
dc.subject.keywordAuthor | additional training process | - |
dc.subject.keywordAuthor | benchmark dataset | - |
dc.subject.keywordAuthor | precision performance | - |
dc.subject.keywordAuthor | state-of-the-art object detection speed | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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