Event Detection Based on Deep Learning Using Audio and Radar Sensors
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Taeho | - |
dc.contributor.author | Noh, Kyoungjin | - |
dc.contributor.author | Kim, Jaeha | - |
dc.contributor.author | Youn, Jeongnam | - |
dc.contributor.author | Chang, Joon Hyuk | - |
dc.date.accessioned | 2021-07-30T05:31:30Z | - |
dc.date.available | 2021-07-30T05:31:30Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2018-11 | - |
dc.identifier.issn | 2374-0272 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/5243 | - |
dc.description.abstract | In this paper, we propose event detection based on deep learning using audio and radar. The proposed event detection technique combines the two deep-learning models based on the audio signal and radar signal. The data set used research is consist of five indoor events., It showed better performance than the event detection using audio or radar single data. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Event Detection Based on Deep Learning Using Audio and Radar Sensors | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chang, Joon Hyuk | - |
dc.identifier.doi | 10.1109/ICNIDC.2018.8525614 | - |
dc.identifier.scopusid | 2-s2.0-85058276736 | - |
dc.identifier.bibliographicCitation | Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018, pp.179 - 182 | - |
dc.relation.isPartOf | Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 | - |
dc.citation.title | Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 | - |
dc.citation.startPage | 179 | - |
dc.citation.endPage | 182 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Digital integrated circuits | - |
dc.subject.keywordPlus | Feature extraction | - |
dc.subject.keywordPlus | Neural networks | - |
dc.subject.keywordPlus | Tracking radar | - |
dc.subject.keywordPlus | Audio signal | - |
dc.subject.keywordPlus | Convolutional neural network | - |
dc.subject.keywordPlus | Ensemble modeling | - |
dc.subject.keywordPlus | Event detection | - |
dc.subject.keywordPlus | Indoor Events | - |
dc.subject.keywordPlus | Learning models | - |
dc.subject.keywordPlus | Radar sensors | - |
dc.subject.keywordPlus | Radar signals | - |
dc.subject.keywordPlus | Deep learning | - |
dc.subject.keywordAuthor | Convolutional Neural Network | - |
dc.subject.keywordAuthor | Deep Learning | - |
dc.subject.keywordAuthor | Ensemble Model | - |
dc.subject.keywordAuthor | Feature Extraction | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8525614 | - |
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