Deep CNN-BiLSTM Model for Transportation Mode Detection Using Smartphone Accelerometer and Magnetometer-Reference-Cited by-同舟云学术

Deep CNN-BiLSTM Model for Transportation Mode Detection Using Smartphone Accelerometer and Magnetometer

Published:2022-06-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Intelligent Vehicles Symposium (IV)
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Author:

Tang Qinrui¹,Jahan Kanwal²,Roth Michael²

Affiliation:

1. Institute of Transportation Systems,German Aerospace Center (DLR),Berlin,Germany

2. Institute of Transportation Systems,German Aerospace Center (DLR),Brunswick,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9826996/9826997/09827275.pdf?arnumber=9827275

Reference27 articles.

1. Learning Transportation Modes From Smartphone Sensors Based on Deep Neural Network

2. Classical and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors

3. A sensors based deep learning model for unseen locomotion mode identification using multiple semantic matrices;mishra;IEEE Transactions on Mobile Computing,2020

4. Top in the Lab, Flop in the Field?

5. Hierarchical Signal Segmentation and Classification for Accurate Activity Recognition

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