Event Detection Based on Deep Learning Using Audio and Radar Sensors
- Authors
- Kim, Taeho; Noh, Kyoungjin; Kim, Jaeha; Youn, Jeongnam; Chang, 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.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/5243)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.