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Found 7 papers, 0 papers with code
CarSpeedNet: A Deep Neural Network-based Car Speed Estimation from Smartphone Accelerometer
In this study, a novel deep neural network (DNN) architecture, CarSpeedNet, is introduced to estimate car speed using three-axis accelerometer data from smartphones.
Learning Position From Vehicle Vibration Using an Inertial Measurement Unit
This paper presents a novel approach to vehicle positioning that operates without reliance on the global navigation satellite system (GNSS).
Deep Learning for Inertial Sensor Alignment
Accurate alignment of a fixed mobile device equipped with inertial sensors inside a moving vehicle is important for navigation, activity recognition, and other applications.
A Hybrid Model and Learning-Based Adaptive Navigation Filter
In most situations, the process noise is covariance assumed to be constant.
Learning Car Speed Using Inertial Sensors for Dead Reckoning Navigation
A deep neural network (DNN) is trained to estimate the speed of a car driving in an urban area using as input a stream of measurements from a low-cost six-axis inertial measurement unit (IMU).
Length Learning for Planar Euclidean Curves
As we know these concepts, we are highly motivated to reconstruct them by using deep neural networks.
Optimal Disturbance Attenuation Approach with Measurement Feedback to Missile Guidance
Pursuit-evasion differential games using the Disturbance Attenuation approach are revisited.
