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DoorINet: Door Heading Prediction Through Inertial Deep Learning
Aleksei Zakharchenko
, Sharon Farber
,
Itzik Klein
Department of Marine Technologies
Research output
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Contribution to journal
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Article
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peer-review
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Dive into the research topics of 'DoorINet: Door Heading Prediction Through Inertial Deep Learning'. Together they form a unique fingerprint.
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Keyphrases
Deep Learning
100%
Heading Angle
100%
Head Movement Prediction
100%
Gyroscope
50%
Magnetometer
50%
Accelerometer
25%
Inertial Sensors
25%
Data-driven Methods
25%
Indoor Environment
25%
Moving Objects
25%
Accelerometer Measurements
25%
System Algorithm
25%
Model-based Approach
25%
Orientation Estimation
25%
Refrigerator
25%
Attitude Angle Estimation
25%
Magnetometer Measurements
25%
Heading Angle Estimation
25%
Low-cost Inertial Sensor
25%
Closet
25%
Walking Pedestrians
25%
Computer Science
Reproducibility
100%
Reference System
100%
Deep Learning Method
100%
Deep Learning Framework
100%
Engineering
Inertial Sensor
100%
Deep Learning Method
100%
Moving Object
50%
Reference System
50%
Cost Efficiency
50%
Attitude Angle
50%
Earth and Planetary Sciences
Accelerometer
100%
Gyroscope
100%
Indoor Environment
50%