Real-time event detection using recurrent neural network in social sensors
Author
Abstract
Suggested Citation
DOI: 10.1177/1550147719856492
Download full text from publisher
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Zuojin Li & Qing Yang & Shengfu Chen & Wei Zhou & Liukui Chen & Lei Song, 2019. "A fuzzy recurrent neural network for driver fatigue detection based on steering-wheel angle sensor data," International Journal of Distributed Sensor Networks, , vol. 15(9), pages 15501477198, September.
- Ping-Huan Kuo & Ssu-Ting Lin & Jun Hu, 2020. "DNAE-GAN: Noise-free acoustic signal generator by integrating autoencoder and generative adversarial network," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
More about this item
Keywords
Social data; neural network; multiple word embedding; event detection; long short-term memory; real-time;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:15:y:2019:i:6:p:1550147719856492. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.