Sensor-Fusion for Smartphone Location Tracking Using Hybrid Multimodal Deep Neural Networks
Many engineered approaches have been proposed over the years for solving the hard problem of performing indoor localization using smartphone sensors. However, specialising these solutions for difficult edge cases remains challenging. Here we propose an end-to-end hybrid multimodal deep neural networ...
Saved in:
Main Authors: | Xijia Wei, Zhiqiang Wei, Valentin Radu |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/f5f97214bfc74fd999d152b1db17ef7f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Indoor Position-Estimation Algorithm Using Smartphone IMU Sensor Data
by: Alwin Poulose, et al.
Published: (2019) -
An Enhanced Pedestrian Visual-Inertial SLAM System Aided with Vanishing Point in Indoor Environments
by: Wennan Chai, et al.
Published: (2021) -
Targeted Aspect-Based Multimodal Sentiment Analysis: An Attention Capsule Extraction and Multi-Head Fusion Network
by: Donghong Gu, et al.
Published: (2021) -
Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
by: Qi Han, et al.
Published: (2021) -
WiFi FTM, UWB and Cellular-Based Radio Fusion for Indoor Positioning
by: Carlos S. Álvarez-Merino, et al.
Published: (2021)