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Event Detection Based on Deep Learning Using Audio and Radar Sensors

Authors
Kim, TaehoNoh, KyoungjinKim, JaehaYoun, JeongnamChang, Joon Hyuk
Issue Date
Nov-2018
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Convolutional Neural Network; Deep Learning; Ensemble Model; Feature Extraction
Citation
Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018, pp.179 - 182
Indexed
SCOPUS
Journal Title
Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018
Start Page
179
End Page
182
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/5243
DOI
10.1109/ICNIDC.2018.8525614
ISSN
2374-0272
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.
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