Underground Localization in 3−D Using Magneto−Inductive Tracking

Underground Localization in 3−D Using Magneto−Inductive Tracking

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Bibliográfalaš dieđut
Váldodahkkit:	Markham, A, Trigoni, N, Macdonald, D, Ellwood, S
Materiálatiipa:	Journal article
Almmustuhtton:	2012

Geahča maid

Underground Localization in 3−D Using Magneto−Inductive Tracking
Dahkki: Markham, A, et al.
Almmustuhtton: (2012)

Revealing the hidden lives of underground animals using magneto-inductive tracking.
Dahkki: Markham, A, et al.
Almmustuhtton: (2010)

Magneto-inductive tracking in underground environments
Dahkki: Abrudan, T, et al.
Almmustuhtton: (2017)

A new Magneto−Inductive tracking technique to uncover subterranean activity: What do animals do underground?
Dahkki: Noonan, M, et al.
Almmustuhtton: (2015)

Underground incrementally deployed magneto-inductive 3-D positioning network
Dahkki: Abrudan, TE, et al.
Almmustuhtton: (2016)

Demo Abstract: Magneto−inductive tracking of underground animals
Dahkki: Ellwood, D
Almmustuhtton: (2010)

Impact of Rocks and Minerals on Underground Magneto-Inductive Communication and Localization
Dahkki: Traian E. Abrudan, et al.
Almmustuhtton: (2016-01-01)

Revealing the hidden lives of underground animals using magneto−inductive tracking
Dahkki: Ellwood, D
Almmustuhtton: (2010)

Magneto-inductive networked rescue system (MINERS): taking sensor networks underground.
Dahkki: Markham, A, et al.
Almmustuhtton: (2012)

Magneto−inductive networked rescue system (MINERS): taking sensor networks underground
Dahkki: Markham, A, et al.
Almmustuhtton: (2012)

Demo: IMU−Aided Magneto−Inductive Localization
Dahkki: Abrudan, T, et al.
Almmustuhtton: (2015)

A Case for Magneto−Inductive Indoor Localization (BEST POSTER AWARD)
Dahkki: Abrudan, T, et al.
Almmustuhtton: (2015)

Distortion rejecting magneto-inductive three-dimensional localization (MagLoc)
Dahkki: Abrudan, T, et al.
Almmustuhtton: (2015)

iMag: Accurate and rapidly deployable inertial magneto-inductive localisation
Dahkki: Wei, B, et al.
Almmustuhtton: (2018)

Sensor fusion for magneto-inductive navigation
Dahkki: Wahlstrom, J, et al.
Almmustuhtton: (2019)

iMag+: an accurate and rapidly deployable inertial magneto-inductive SLAM system
Dahkki: Wei, B, et al.
Almmustuhtton: (2021)

Reducing Magneto-Inductive Positioning Errors in a Metal-Rich Indoor Environment
Dahkki: Kypris, O, et al.
Almmustuhtton: (2016)

Tracking people in highly dynamic industrial environments
Dahkki: Papaioannou, S, et al.
Almmustuhtton: (2016)

Sample, crop, track: self-supervised mobile 3D object detectionfor urban driving LiDAR
Dahkki: Shin, S, et al.
Almmustuhtton: (2023)

3D motion tracking display enabled by magneto-interactive electroluminescence
Dahkki: Seung Won Lee, et al.
Almmustuhtton: (2020-11-01)

Demo: Lightweight continuous indoor tracking system
Dahkki: Xiao, Z, et al.
Almmustuhtton: (2014)

Robust attentional aggregation of deep feature sets for multi-view 3D reconstruction
Dahkki: Yang, B, et al.
Almmustuhtton: (2019)

Magneto Inductive (MI) Channel Variables Prediction Through Machine Learning Linear Regression Method, for Underwater and Underground WSNs
Dahkki: Aman Muhammad, et al.
Almmustuhtton: (2025-01-01)

Discrete Gene Regulatory Networks (dGRNs): A novel approach to configuring sensor networks
Dahkki: Markham, A, et al.
Almmustuhtton: (2010)

Lightweight map matching for indoor localization using conditional random fields (BEST PAPER)
Dahkki: Xiao, Z, et al.
Almmustuhtton: (2014)

Discrete Gene Regulatory Networks (dGRNs): A novel approach to configuring sensor networks
Dahkki: Markham, A, et al.
Almmustuhtton: (2010)

Poster: WiFi sensors meet visual tracking for an accurate positioning system
Dahkki: Papaioannou, S, et al.
Almmustuhtton: (2014)

Dense 3D object reconstruction from a single depth view
Dahkki: Yang, B, et al.
Almmustuhtton: (2018)

Spherical mask: coarse-to-fine 3D point cloud instance segmentation with spherical representation
Dahkki: Shin, S, et al.
Almmustuhtton: (2024)

Magneto-inductive wave data communications systems
Dahkki: Chan, C
Almmustuhtton: (2014)

Magnetic Metamaterials as 1-D Data Transfer Channels: An Application for Magneto-Inductive Waves
Dahkki: Stevens, C, et al.
Almmustuhtton: (2010)

Magnetic metamaterials as 1-D data transfer channels: An application for magneto-inductive waves
Dahkki: Stevens, C, et al.
Almmustuhtton: (2010)

Increasing the efficiency of 6-DoF visual localization using multi-modal sensory data
Dahkki: Clark, R, et al.
Almmustuhtton: (2017)

Power waves and scattering parameters in magneto-inductive systems
Dahkki: A. Voronov, et al.
Almmustuhtton: (2021-04-01)

3D-PhysNet: Learning the intuitive physics of non-rigid object deformations
Dahkki: Wang, Z, et al.
Almmustuhtton: (2018)

WILDSENSING: Design and deployment of a sustainable sensor network for wildlife monitoring.
Dahkki: Dyo, V, et al.
Almmustuhtton: (2012)

Evolution and sustainability of a wildlife monitoring sensor network.
Dahkki: Dyo, V, et al.
Almmustuhtton: (2010)

Climate and the individual: inter-annual variation in the autumnal activity of the European badger (Meles meles).
Dahkki: Michael J Noonan, et al.
Almmustuhtton: (2014-01-01)

3D object reconstruction from a single depth view with adversarial learning
Dahkki: Yang, B, et al.
Almmustuhtton: (2018)

Evaluation of Retained Austenite in Carburized Bearing Steel Using Magneto-Inductive Method
Dahkki: Laura G. Ionescu, et al.
Almmustuhtton: (2023-07-01)