Skip to main navigation
Skip to search
Skip to main content
University of Haifa Home
Update your profile
Home
Researchers
Research units
Research output
Search by expertise, name or affiliation
Learning Car Speed Using Inertial Sensors for Dead Reckoning Navigation
Maxim Freydin, Barak Or
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Learning Car Speed Using Inertial Sensors for Dead Reckoning Navigation'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Training Model
100%
Inertial Sensors
100%
Global Navigation Satellite System
100%
Inertial Measurement Unit
100%
Dead Reckoning Navigation
100%
Car Speed
100%
Urban Areas
50%
Israel
50%
Dead Reckoning
50%
Speed Estimation
50%
Position Accuracy
50%
Angular Velocity
50%
Position Updating
50%
Deep Neural Network
50%
Nonlinear Relation
50%
Deep Learning Architectures
50%
Ground-truth Labels
50%
Long Short-term Memory
50%
Position Measurement
50%
Storage Layer
50%
Localization Scheme
50%
Real-time Kinematic (RTK) Positioning
50%
Positioning Device
50%
Car Driving
50%
Acceleration Velocity
50%
Six-axis
50%
Pseudo-measurements
50%
Engineering
Inertial Sensor
100%
Units of Measurement
100%
Inertial Measurement
100%
Deep Neural Network
100%
Angular Velocity ω
50%
Neural Network Architecture
50%
Real System
50%
Long Short-Term Memory
50%