Jan 24, 2024 · We propose DoorINet, an end-to-end deep-learning framework to calculate the heading angle from door-mounted, low-cost inertial sensors without using ...
To cope with low magnetometer performance in an indoor enthronement, we propose DoorINet, a deep-learning, end-to-end framework for estimating the heading angle ...
This repository contains the dataset, source code and pretrained weights for DoorINet architecture introduced in the paper DoorINet: A Deep Learning Inertial ...
Feb 16, 2024 · DoorINet: A Deep-Learning Inertial Framework for Door-Mounted IoT Applications. ... Inertial sensors are widely used in a variety of applications.
Oct 22, 2024 · We propose DoorINet, an end-to-end deep-learning framework to calculate the heading angle from door-mounted, low-cost inertial sensors without using ...
DoorINet: A Deep-Learning Inertial Framework for Door-Mounted IoT Applications ... Relying on the gyroscope readings, the accelerometer readings are used to ...
Aleksei Zakharchenko, Sharon Farber, Itzik Klein: DoorINet: A Deep-Learning Inertial Framework for Door-Mounted IoT Applications. CoRR abs/2402.09427 (2024).
To circumvent such situations, we propose DoorINet, an end-to-end deep-learning framework to calculate the heading angle from door-mounted, low-cost inertial ...
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This paper presents a novel end-to-end deep learning framework for real-time inertial attitude estimation using 6DoF IMU measurements that incorporates ...
This article proposes a hybrid deep learning and model-based solution for attitude estimation using the smartphone's inertial sensors that uses a unique ...