Andrew Markham : Publications
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[1]
3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar
N. Trigoni Z.Peijun C.X. Lu B. Wang and A. Markham
In IEEE International Conference on Robotics and Automation (ICRA). 2021.
Details about 3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar | BibTeX data for 3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar | Download (pdf) of 3D Motion Capture of an Unmodified Drone with Single−Chip Millimeter Wave Radar
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[2]
3D Object Dense Reconstruction from a Single Depth View with Adversarial Learning
Bo Yang‚ Hongkai Wen‚ Sen Wang‚ Ronald Clark‚ Andrew Markham and Niki Trigoni
In International Conference on Computer Vision (ICCV) Workshops. 2017.
Details about 3D Object Dense Reconstruction from a Single Depth View with Adversarial Learning | BibTeX data for 3D Object Dense Reconstruction from a Single Depth View with Adversarial Learning | Download (pdf) of 3D Object Dense Reconstruction from a Single Depth View with Adversarial Learning | DOI (10.1109/ICCVW.2017.86)
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[3]
3D−PhysNet: Learning the Intuitive Physics of Non−Rigid Object Deformations
Zhihua Wang‚ Stefano Rosa‚ Bo Yang‚ Sen Wang‚ Niki Trigoni and Andrew Markham
In 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence IJCAI−ECAI. 2018.
Details about 3D−PhysNet: Learning the Intuitive Physics of Non−Rigid Object Deformations | BibTeX data for 3D−PhysNet: Learning the Intuitive Physics of Non−Rigid Object Deformations | Download (pdf) of 3D−PhysNet: Learning the Intuitive Physics of Non−Rigid Object Deformations
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[4]
A Case for Magneto−Inductive Indoor Localization (BEST POSTER AWARD)
T. E. Abrudan‚ A. Markham and N. Trigoni
In The 11th European Conference on Wireless Sensor Networks (EWSN 2014). Oxford‚ UK. 2014.
Details about A Case for Magneto−Inductive Indoor Localization (BEST POSTER AWARD) | BibTeX data for A Case for Magneto−Inductive Indoor Localization (BEST POSTER AWARD) | Download (pdf) of A Case for Magneto−Inductive Indoor Localization (BEST POSTER AWARD)
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[5]
A biomimetic ranking system for energy constrained mobile wireless sensor networks
A. C. Markham and A. J. Wilkinson
In Southern African Telecommunications‚ Networks and Applications Conference (SATNAC)‚ Mauritius‚ 9−13 September 2007. 2007.
Details about A biomimetic ranking system for energy constrained mobile wireless sensor networks | BibTeX data for A biomimetic ranking system for energy constrained mobile wireless sensor networks | Download (pdf) of A biomimetic ranking system for energy constrained mobile wireless sensor networks
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[6]
A new Magneto−Inductive tracking technique to uncover subterranean activity: What do animals do underground?
Michael J. Noonan‚ Andrew Markham‚ Chris Newman‚ Niki Trigoni‚ Christina D. Buesching‚ Stephen A. Ellwood and David W. Macdonald
In Methods in Ecology and Evolution. 2015.
Details about A new Magneto−Inductive tracking technique to uncover subterranean activity: What do animals do underground? | BibTeX data for A new Magneto−Inductive tracking technique to uncover subterranean activity: What do animals do underground? | DOI (10.1111/2041-210X.12348)
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[7]
A new Magneto‐Inductive tracking technique to uncover subterranean activity: what do animals do underground?
David W Macdonald Michael J Noonan Andrew Markham Chris Newman Niki Trigoni Christina D Buesching Stephen A Ellwood
In Methods in Ecology and Evolution‚ Vol. 6‚ Issue 5. 2015.
Details about A new Magneto‐Inductive tracking technique to uncover subterranean activity: what do animals do underground? | BibTeX data for A new Magneto‐Inductive tracking technique to uncover subterranean activity: what do animals do underground?
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[8]
Accuracy Estimation For Sensor Systems
Hongkai Wen‚ Zhuoling Xiao‚ Andrew Markham and Niki Trigoni
In IEEE Transaction on Mobile Computing. 2015.
Details about Accuracy Estimation For Sensor Systems | BibTeX data for Accuracy Estimation For Sensor Systems | Download (pdf) of Accuracy Estimation For Sensor Systems
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[9]
Accurate Positioning via Cross Modality Training
S. Papaioannou‚ H. Wen‚ Z. Xiao‚ A. Markham and N. Trigoni
In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems. Pages 239−251. 2015.
Details about Accurate Positioning via Cross Modality Training | BibTeX data for Accurate Positioning via Cross Modality Training | Download (pdf) of Accurate Positioning via Cross Modality Training
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[10]
Adaptive Social Hierarchies: From Nature to Networks
A. C. Markham
In Yang Xiao and Fei Hu, editors, Bio−inspired Computing and Communication Networks. Auerbach Publications‚ Taylor Taylor & Francis Group. 2008.
Details about Adaptive Social Hierarchies: From Nature to Networks | BibTeX data for Adaptive Social Hierarchies: From Nature to Networks | Download (pdf) of Adaptive Social Hierarchies: From Nature to Networks
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[11]
Advances and Challenges in Underground Sensing
Christian Wietfeld Suk−Un Yoon Andrew Markham Niki Trigoni Traian E Abrudan Orfeas Kypris
In Underground Sensing. Chapter Advances and Challenges in Underground Sensing. 2017.
Details about Advances and Challenges in Underground Sensing | BibTeX data for Advances and Challenges in Underground Sensing
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[12]
An active‐radio‐frequency‐identification system capable of identifying co‐locations and social‐structure: Validation with a wild free‐ranging animal
David W Macdonald Stephen A Ellwood Chris Newman Robert A Montgomery Vincenzo Nicosia Christina D Buesching Andrew Markham Cecilia Mascolo Niki Trigoni Bence Pasztor Vladimir Dyo Vito Latora Sandra E Baker
In Methods in Ecology and Evolution‚ vol. 8‚ issue 12. 2017.
Details about An active‐radio‐frequency‐identification system capable of identifying co‐locations and social‐structure: Validation with a wild free‐ranging animal | BibTeX data for An active‐radio‐frequency‐identification system capable of identifying co‐locations and social‐structure: Validation with a wild free‐ranging animal | Download (pdf) of An active‐radio‐frequency‐identification system capable of identifying co‐locations and social‐structure: Validation with a wild free‐ranging animal
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[13]
AtLoc: Attention Guided Camera Localization
Bing Wang‚ Changhao Chen‚ Chris Xiaoxuan Lu‚ Peijun Zhao‚ Niki Trigoni and Andrew Markham
In The Thirty−Fourth AAAI Conference on Artificial Intelligence. 2020.
Details about AtLoc: Attention Guided Camera Localization | BibTeX data for AtLoc: Attention Guided Camera Localization | Download (pdf) of AtLoc: Attention Guided Camera Localization
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[14]
Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues
Chris Xiaoxuan Lu‚ Xuan Kan‚ Bowen Du‚ Changhao Chen‚ Hongkai Wen‚ Andrew Markham‚ Niki Trigoni and John Stankovic
In The Web Conference (WWW). 2019.
Details about Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues | BibTeX data for Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues | Download (pdf) of Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues
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[15]
Autonomous Learning of Speaker Identity and WiFi Geofence from Noisy Sensor Data
Chris Xiaoxuan Lu‚ Yuanbo Xiangli‚ Peijun Zhao‚ Changhao Chen‚ Niki Trigoni and Andrew Markham
In IEEE Internet of Things Journal. 2019.
Details about Autonomous Learning of Speaker Identity and WiFi Geofence from Noisy Sensor Data | BibTeX data for Autonomous Learning of Speaker Identity and WiFi Geofence from Noisy Sensor Data | Download (pdf) of Autonomous Learning of Speaker Identity and WiFi Geofence from Noisy Sensor Data
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[16]
Beyond Fusion: Modality Hallucination−based Multispectral Fusion for Pedestrian Detection
Qian Xie‚ Ta−Ying Cheng‚ Jia−Xing Zhong‚ Kaichen Zhou‚ Andrew Markham and Niki Trigoni
In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2023.
Details about Beyond Fusion: Modality Hallucination−based Multispectral Fusion for Pedestrian Detection | BibTeX data for Beyond Fusion: Modality Hallucination−based Multispectral Fusion for Pedestrian Detection | Download (pdf) of Beyond Fusion: Modality Hallucination−based Multispectral Fusion for Pedestrian Detection
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[17]
Characterization of Non−Line−of−Sight (NLOS) Bias via Analysis of Clutter Topology
Muzammil Hussain‚ Yusuf Aytar‚ Andrew Markham and Niki Trigoni
In IEEE/ION Poisition Location and Navigation Symposium (PLANS) 2012. 2012.
Details about Characterization of Non−Line−of−Sight (NLOS) Bias via Analysis of Clutter Topology | BibTeX data for Characterization of Non−Line−of−Sight (NLOS) Bias via Analysis of Clutter Topology | Download (pdf) of Characterization of Non−Line−of−Sight (NLOS) Bias via Analysis of Clutter Topology
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[18]
Climate and the Individual: Inter−Annual Variation in the Autumnal Activity of the European Badger
M. Noonan‚ A. Markham‚ C. Newman‚ N. Trigoni‚ C. Buesching‚ S. Ellwood and D. Macdonald
In PLOS ONE. 2014.
Details about Climate and the Individual: Inter−Annual Variation in the Autumnal Activity of the European Badger | BibTeX data for Climate and the Individual: Inter−Annual Variation in the Autumnal Activity of the European Badger | Link to Climate and the Individual: Inter−Annual Variation in the Autumnal Activity of the European Badger
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[19]
Comparison of Accuracy Estimation Approaches for Sensor Networks
Hongkai Wen‚ Zhuoling Xiao‚ Andrew Symington‚ Andrew Markham and Niki Trigoni
In the 9th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'13). Pages 28−35. 2013.
Details about Comparison of Accuracy Estimation Approaches for Sensor Networks | BibTeX data for Comparison of Accuracy Estimation Approaches for Sensor Networks | Link to Comparison of Accuracy Estimation Approaches for Sensor Networks
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[20]
Deep Learning based Pedestrian Inertial Navigation: Methods‚ Dataset and On−Device Inference
Changhao Chen‚ Peijun Zhao‚ Chris Xiaoxuan Lu‚ Wei Wang‚ Andrew Markham and Niki Trigoni
In IEEE Internet of Things Journal. 2020.
Details about Deep Learning based Pedestrian Inertial Navigation: Methods‚ Dataset and On−Device Inference | BibTeX data for Deep Learning based Pedestrian Inertial Navigation: Methods‚ Dataset and On−Device Inference | Download (pdf) of Deep Learning based Pedestrian Inertial Navigation: Methods‚ Dataset and On−Device Inference
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[21]
Deep Neural Network Based Inertial Odometry Using Low−cost Inertial Measurement Units
Changhao Chen‚ Chris Xiaoxuan Lu‚ Johan Wahlstrom‚ Andrew Markham and Niki Trigoni
In IEEE Transactions on Mobile Computing. 2020.
Details about Deep Neural Network Based Inertial Odometry Using Low−cost Inertial Measurement Units | BibTeX data for Deep Neural Network Based Inertial Odometry Using Low−cost Inertial Measurement Units | Download (pdf) of Deep Neural Network Based Inertial Odometry Using Low−cost Inertial Measurement Units
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[22]
DeepAuth: In−situ Authentication for Smartwatches via Deeply Learned Behavioural Biometrics
Chris Xiaoxuan Lu‚ Bowen Du‚ Peijun Zhao‚ Hongkai Wen‚ Yiran Shen‚ Andrew Markham and Niki Trignoni
In International Symposium on Wearable Computers (ISWC). 2018.
Details about DeepAuth: In−situ Authentication for Smartwatches via Deeply Learned Behavioural Biometrics | BibTeX data for DeepAuth: In−situ Authentication for Smartwatches via Deeply Learned Behavioural Biometrics | Download (pdf) of DeepAuth: In−situ Authentication for Smartwatches via Deeply Learned Behavioural Biometrics
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[23]
DeepPCO: End−to−end Point Cloud Odometry through Deep Parallel Neural Network
Wei Wang Muhamad Risqi U. Saputra Peijun Zhao Pedro Gusmao Bo Yang Changhao Chen Andrew Markham and Niki Trigoni
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2019.
Details about DeepPCO: End−to−end Point Cloud Odometry through Deep Parallel Neural Network | BibTeX data for DeepPCO: End−to−end Point Cloud Odometry through Deep Parallel Neural Network | Download (pdf) of DeepPCO: End−to−end Point Cloud Odometry through Deep Parallel Neural Network
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[24]
DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination
M.R.U. Saputra P.P.B. de Gusmao C.X. Lu Y. Almalioglu S. Rosa C. Chen J. Wahlstrom W. Wang A. Markham and N. Trigoni
In IEEE Robotics and Automation Letters (RAL) + IEEE ICRA. 2020.
Details about DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination | BibTeX data for DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination | Download (pdf) of DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination
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[25]
Defo−Net: Learning body deformation using generative adversarial networks
N. Trigoni Z. Wang S. Rosa L. Xie B. Yang S. Wang and A. Markham
In IEEE Intl Conference on Robotics and Automation (ICRA). 2018.
Details about Defo−Net: Learning body deformation using generative adversarial networks | BibTeX data for Defo−Net: Learning body deformation using generative adversarial networks | Download of Defo−Net: Learning body deformation using generative adversarial networks
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[26]
Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers
Chris Xiaoxuan Lu‚ Peijun Zhao‚ Bowen Du‚ Hongkai Wen‚ Andrew Markham‚ Stefano Rosa and Niki Trignoni
In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems (SenSys). 2018.
Details about Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers | BibTeX data for Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers | Download (pdf) of Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers
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[27]
Demo Abstract: Magneto−inductive tracking of underground animals
Andrew Markham‚ Niki Trigoni‚ Stephen A. Ellwood and David W. Macdonald
In 8th ACM Conference on Embedded Networked Sensor Systems (Sensys 2010). Zurich‚ Switzerland. November, 2010.
Details about Demo Abstract: Magneto−inductive tracking of underground animals | BibTeX data for Demo Abstract: Magneto−inductive tracking of underground animals | Download (pdf) of Demo Abstract: Magneto−inductive tracking of underground animals
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[28]
Demo: Lightweight continuous indoor tracking system
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In 11th European Conference on Wireless Sensor Networks (EWSN'14). Oxford‚ UK. 2014.
Details about Demo: Lightweight continuous indoor tracking system | BibTeX data for Demo: Lightweight continuous indoor tracking system | Download (pdf) of Demo: Lightweight continuous indoor tracking system
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[29]
Demo: IMU−Aided Magneto−Inductive Localization
T. E. Abrudan‚ Zhuoling Xiao‚ A. Markham and N. Trigoni
In Microsoft Indoor Localization Competition‚ at the 13th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2014). Berlin‚ Germany. 2014.
Details about Demo: IMU−Aided Magneto−Inductive Localization | BibTeX data for Demo: IMU−Aided Magneto−Inductive Localization
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[30]
Dense 3D Object Reconstruction from a Single Depth View
Bo Yang‚ Stefano Rosa‚ Andrew Markham‚ Niki Trigoni and Hongkai Wen
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2018.
Details about Dense 3D Object Reconstruction from a Single Depth View | BibTeX data for Dense 3D Object Reconstruction from a Single Depth View | Download (pdf) of Dense 3D Object Reconstruction from a Single Depth View | DOI (10.1109/TPAMI.2018.2868195)
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[31]
Discrete Gene Regulatory Networks (dGRNs): A novel approach to configuring sensor networks
Andrew Markham and Niki Trigoni
In Proceedings of the 29th Conference on Computer Communications (InfoCom 2010). March, 2010.
Details about Discrete Gene Regulatory Networks (dGRNs): A novel approach to configuring sensor networks | BibTeX data for Discrete Gene Regulatory Networks (dGRNs): A novel approach to configuring sensor networks | Download of Discrete Gene Regulatory Networks (dGRNs): A novel approach to configuring sensor networks
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[32]
Distilling Knowledge From a Deep Pose Regressor Network
Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Yasin Almalioglu Andrew Markham and Niki Trigoni
In IEEE/CVF International Conference on Computer Vision (ICCV). 2019.
Details about Distilling Knowledge From a Deep Pose Regressor Network | BibTeX data for Distilling Knowledge From a Deep Pose Regressor Network | Download of Distilling Knowledge From a Deep Pose Regressor Network
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[33]
Distortion Rejecting Magneto−inductive 3−D Localization (MagLoc)
Train Abrudan‚ Zhuoling Xiao‚ Andrew Markham and Niki Trigoni
In IEEE Journal on Selected Areas in Communications. No. 33(11). Pages 2404−2417. 2015.
Details about Distortion Rejecting Magneto−inductive 3−D Localization (MagLoc) | BibTeX data for Distortion Rejecting Magneto−inductive 3−D Localization (MagLoc) | Download (pdf) of Distortion Rejecting Magneto−inductive 3−D Localization (MagLoc)
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[34]
EcoLocate: A heterogeneous wireless network system for wildlife tracking
A. C. Markham and A. J. Wilkinson
In International Joint Conferences on Computer‚ Information and Systems Sciences and Engineering (CISSE). 2007.
Details about EcoLocate: A heterogeneous wireless network system for wildlife tracking | BibTeX data for EcoLocate: A heterogeneous wireless network system for wildlife tracking | Download (pdf) of EcoLocate: A heterogeneous wireless network system for wildlife tracking
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[35]
Effect of rainfall on link quality in an outdoor forest deployment
Andrew Markham‚ Niki Trigoni and Stephen A. Ellwood
In Proceedings of the International Conference on Wireless Information Networks and Systems‚ Athens‚ Greece. July, 2010.
Details about Effect of rainfall on link quality in an outdoor forest deployment | BibTeX data for Effect of rainfall on link quality in an outdoor forest deployment | Download (pdf) of Effect of rainfall on link quality in an outdoor forest deployment
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[36]
Evolution and Sustainability of a Wildlife Monitoring Sensor Network
V. Dyo‚ S. Ellwood‚ D. Macdonald‚ A. Markham‚ C. Mascolo‚ B. Pasztor‚ S. Scellato‚ N. Trigoni‚ R. Wohlers and K. Yousef
In 8th ACM Conference on Embedded Networked Sensor Systems (SenSys 2010)‚ Zurich‚ Switzerland. 2010.
Details about Evolution and Sustainability of a Wildlife Monitoring Sensor Network | BibTeX data for Evolution and Sustainability of a Wildlife Monitoring Sensor Network | Download (pdf) of Evolution and Sustainability of a Wildlife Monitoring Sensor Network
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[37]
FootSLAM meets Adaptive Thresholding
Johan Wahlström‚ Andrew Markham and Niki Trigoni
In IEEE Sensors Journal. 2020.
Details about FootSLAM meets Adaptive Thresholding | BibTeX data for FootSLAM meets Adaptive Thresholding
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[38]
Fusion of Radio and Camera Sensor Data for Accurate Indoor Positioning
Savvas Papaioannou‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In the 11th IEEE International Conference on Mobile Ad hoc and Sensor Systems (MASS'14). Pages 109−117. 2014.
Details about Fusion of Radio and Camera Sensor Data for Accurate Indoor Positioning | BibTeX data for Fusion of Radio and Camera Sensor Data for Accurate Indoor Positioning | Link to Fusion of Radio and Camera Sensor Data for Accurate Indoor Positioning
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[39]
GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks
Y. Almalioglu M. R. U. Saputra P. P. de Gusmao A. Markham and N. Trigoni
In IEEE International Conference on Robotics and Automation (ICRA). 2019.
Details about GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks | BibTeX data for GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks | Download (pdf) of GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks
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[40]
GraphTinker: Outlier Rejection and Inlier Injection for Pose Graph SLAM
Linhai Xie‚ Sen Wang‚ Andrew Markham and Niki Trigoni
In Intelligent Robots and Systems (IROS)‚ 2017 IEEE/RSJ International Conference on. IEEE. 2017.
Details about GraphTinker: Outlier Rejection and Inlier Injection for Pose Graph SLAM | BibTeX data for GraphTinker: Outlier Rejection and Inlier Injection for Pose Graph SLAM | Download (pdf) of GraphTinker: Outlier Rejection and Inlier Injection for Pose Graph SLAM
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[41]
Heart Rate Sensing with a Robot Mounted mmWave Radar
Peijun Zhao‚ Chris Xiaoxuan Lu‚ Bing Wang‚ Changhao Chen‚ Linhai Xie‚ Mengyu Wang‚ Niki Trigoni and Andrew Markham
In International Conference on Robotics and Automation (ICRA). 2020.
Details about Heart Rate Sensing with a Robot Mounted mmWave Radar | BibTeX data for Heart Rate Sensing with a Robot Mounted mmWave Radar | Download (pdf) of Heart Rate Sensing with a Robot Mounted mmWave Radar
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[42]
Human tracking and identification through a millimeter wave radar
Peijun Zhao‚ Chris Xiaoxuan Lu‚ Jianan Wang‚ Changhao Chen‚ Wei Wang‚ Niki Trigoni and Andrew Markham
In Ad Hoc Networks Elsevier. 2021.
Details about Human tracking and identification through a millimeter wave radar | BibTeX data for Human tracking and identification through a millimeter wave radar
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[43]
IONet: Learning to Cure the Curse of Drift in Inertial Odometry
Changhao Chen‚ Chris Xiaoxuan Lu‚ Andrew Markham and Niki Trigoni
In The Thirty−Second AAAI Conference on Artificial Intelligence (AAAI−18). 2018.
Details about IONet: Learning to Cure the Curse of Drift in Inertial Odometry | BibTeX data for IONet: Learning to Cure the Curse of Drift in Inertial Odometry | Download (pdf) of IONet: Learning to Cure the Curse of Drift in Inertial Odometry
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[44]
Identification and mitigation of non−line−of−sight conditions using received signal strength
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham‚ Niki Trigoni‚ Phil Blunsom and Jeff Frolik
In IEEE International Conference on Wireless and Mobile Computing‚ Networking and Communications (WiMob'13). Pages 667−674. Lyon‚ France. 2013.
Details about Identification and mitigation of non−line−of−sight conditions using received signal strength | BibTeX data for Identification and mitigation of non−line−of−sight conditions using received signal strength | Download (pdf) of Identification and mitigation of non−line−of−sight conditions using received signal strength
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[45]
Illumination−Aware Hallucination−Based Domain Adaptation for Thermal Pedestrian Detection
Qian Xie‚ Ta−Ying Cheng‚ Zhuangzhuang Dai‚ Vu Tran‚ Niki Trigoni and Andrew Markham
In IEEE Transactions on Intelligent Transportation. 2023.
Details about Illumination−Aware Hallucination−Based Domain Adaptation for Thermal Pedestrian Detection | BibTeX data for Illumination−Aware Hallucination−Based Domain Adaptation for Thermal Pedestrian Detection | Download (pdf) of Illumination−Aware Hallucination−Based Domain Adaptation for Thermal Pedestrian Detection
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[46]
Impact of Rocks and Minerals on Underground Magneto−Inductive Communication and Localization
T. Abrudan‚ O. Kypris‚ N. Trigoni and A. Markham
In IEEE Access arXiv preprint arXiv:1606.03065. 2016.
Details about Impact of Rocks and Minerals on Underground Magneto−Inductive Communication and Localization | BibTeX data for Impact of Rocks and Minerals on Underground Magneto−Inductive Communication and Localization | Download (pdf) of Impact of Rocks and Minerals on Underground Magneto−Inductive Communication and Localization
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[47]
Increasing the efficiency of 6−DoF visual localization using multi−modal sensory data
Ronald Clark‚ Sen Wang‚ Hongkai Wen‚ Niki Trigoni and Andrew Markham
In IEEE−RAS 16th International Conference on Humanoid Robots. 2016.
Details about Increasing the efficiency of 6−DoF visual localization using multi−modal sensory data | BibTeX data for Increasing the efficiency of 6−DoF visual localization using multi−modal sensory data | Download Increasing the Efficiency of 6-DoF Visual Localization Using Multi-Modal.pdf of Increasing the efficiency of 6−DoF visual localization using multi−modal sensory data | Download PublicationFile of Increasing the efficiency of 6−DoF visual localization using multi−modal sensory data
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[48]
Indoor tracking using undirected graphical models
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In IEEE Transactions on Mobile Computing. Vol. 1. No. 1. Pages PP. 2015.
Details about Indoor tracking using undirected graphical models | BibTeX data for Indoor tracking using undirected graphical models | Download (pdf) of Indoor tracking using undirected graphical models
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[49]
Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning
Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Sen Wang Andrew Markham and Niki Trigoni
In IEEE International Conference on Robotics and Automation (ICRA). 2019.
Details about Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning | BibTeX data for Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning | Download (pdf) of Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning
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[50]
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
Bo Yang‚ Jianan Wang‚ Ronald Clark‚ Qingyong Hu‚ Sen Wang‚ Andrew Markham and Niki Trigoni
In Conference on Neural Information Processing Systems (NeurIPS Spotlight). 2019.
Details about Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds | BibTeX data for Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds | Download (pdf) of Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds | Link to Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
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[51]
Learning Semantic Segmentation of Large−Scale Point Clouds with Random Sampling
N.i Trigoni Q. Hu B. Yang L. Xie S. Rosa Y. Guo Z. Wang and A. Markham
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2021.
Details about Learning Semantic Segmentation of Large−Scale Point Clouds with Random Sampling | BibTeX data for Learning Semantic Segmentation of Large−Scale Point Clouds with Random Sampling
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[52]
Learning with Stochastic Guidance for Robot Navigation
Linhai Xie‚ Yishu Miao‚ Sen Wang‚ Phil Blunsom‚ Zhihua Wang‚ Changhao Cheng‚ Andrew Markham and Niki Trigoni
In IEEE Transactions on Neural Networks and Learning Systems (TNNLS). IEEE. 2020.
accepted
Details about Learning with Stochastic Guidance for Robot Navigation | BibTeX data for Learning with Stochastic Guidance for Robot Navigation | Download (pdf) of Learning with Stochastic Guidance for Robot Navigation
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[53]
Learning with training wheels: Speeding up training with a simple controller for deep reinforcement learning
N Trigoni L Xie S Wang S Rosa AC Markham
In IEEE Intl Conference on Robotics and Automation (ICRA). 2018.
Details about Learning with training wheels: Speeding up training with a simple controller for deep reinforcement learning | BibTeX data for Learning with training wheels: Speeding up training with a simple controller for deep reinforcement learning | Download (pdf) of Learning with training wheels: Speeding up training with a simple controller for deep reinforcement learning
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[54]
Lightweight map matching for indoor localization using conditional random fields (BEST PAPER)
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In The International Conference on Information Processing in Sensor Networks (IPSN'14). Berlin‚ Germany. 2014.
Details about Lightweight map matching for indoor localization using conditional random fields (BEST PAPER) | BibTeX data for Lightweight map matching for indoor localization using conditional random fields (BEST PAPER) | Link to Lightweight map matching for indoor localization using conditional random fields (BEST PAPER)
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[55]
Magneto−Inductive Underground Tracking: Principles and Systems
T. Abrudan‚ O. Kypris‚ N. Trigoni and A. Markham
In Elsevier, editor, Underground Sensing: Monitoring and hazard detection for environment and infrastructure − 1st edition. Chapter 8.2. 2016.
Details about Magneto−Inductive Underground Tracking: Principles and Systems | BibTeX data for Magneto−Inductive Underground Tracking: Principles and Systems | Download (pdf) of Magneto−Inductive Underground Tracking: Principles and Systems
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[56]
Magneto−inductive networked rescue system (MINERS): taking sensor networks underground
Andrew Markham and Niki Trigoni
In 11th International Conference on Information Processing in Sensor Networks (IPSN). 2012.
Details about Magneto−inductive networked rescue system (MINERS): taking sensor networks underground | BibTeX data for Magneto−inductive networked rescue system (MINERS): taking sensor networks underground | Download (pdf) of Magneto−inductive networked rescue system (MINERS): taking sensor networks underground
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[57]
MotionTransformer: Transferring Neural Inertial Tracking Between Domains
Changhao Chen‚ Yishu Miao‚ Chris Xiaoxuan Lu‚ Linhai Xie‚ Phil Blunsom‚ Andrew Markham and Niki Trigoni
In The Thirty−Third AAAI Conference on Artificial Intelligence (AAAI−19). 2019.
Details about MotionTransformer: Transferring Neural Inertial Tracking Between Domains | BibTeX data for MotionTransformer: Transferring Neural Inertial Tracking Between Domains | Download (pdf) of MotionTransformer: Transferring Neural Inertial Tracking Between Domains
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[58]
Non−line−of−sight identification and mitigation using received signal strength
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham‚ Niki Trigoni‚ Phil Blunsom and J. Frolik
In IEEE Transactions on Wireless Communications. 2015.
Details about Non−line−of−sight identification and mitigation using received signal strength | BibTeX data for Non−line−of−sight identification and mitigation using received signal strength | Download (pdf) of Non−line−of−sight identification and mitigation using received signal strength
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[59]
On a Wildlife Tracking and Telemetry System: A Wireless Network Approach
Andrew Markham
PhD Thesis University of Cape Town‚ South Africa. 2008.
Details about On a Wildlife Tracking and Telemetry System: A Wireless Network Approach | BibTeX data for On a Wildlife Tracking and Telemetry System: A Wireless Network Approach | Download (pdf) of On a Wildlife Tracking and Telemetry System: A Wireless Network Approach
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[60]
PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization
Wei Wang‚ Bing Wang‚ Peijun Zhao‚ Changhao Chen‚ Ronald Clark‚ Bo Yang‚ Andrew Markham and Niki Trigoni
In IEEE Sensors Journal. 2021.
Details about PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization | BibTeX data for PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization | Download (pdf) of PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization
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[61]
Poster Abstract: Towards Self−supervised Face Labeling via Cross−modality Association
Chris Xiaoxuan Lu‚ Xuan Kan‚ Stefano Rosa‚ Bowen Du‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems (SenSys). 2017.
Details about Poster Abstract: Towards Self−supervised Face Labeling via Cross−modality Association | BibTeX data for Poster Abstract: Towards Self−supervised Face Labeling via Cross−modality Association | Download (pdf) of Poster Abstract: Towards Self−supervised Face Labeling via Cross−modality Association
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[62]
Poster Abstract: Wildlife and Environmental Monitoring using RFID and WSN Technology
Vladimir Dyo‚ Stephen A. Ellwood‚ David W. Macdonald‚ Andrew Markham‚ Cecilia Mascolo‚ Bence Pasztor‚ Niki Trigoni and Ricklef Wohlers
In The 7th ACM Conference on Embedded Networked Sensor Systems (SenSys09). Berkeley‚ California‚. 2009.
Details about Poster Abstract: Wildlife and Environmental Monitoring using RFID and WSN Technology | BibTeX data for Poster Abstract: Wildlife and Environmental Monitoring using RFID and WSN Technology
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[63]
Poster: WiFi sensors meet visual tracking for an accurate positioning system
Savvas Papaioannou‚ Hongkai Wen‚ Zhuoling Xiao‚ Andrew Markham and Niki Trigoni
In 11th European Conference on Wireless Sensor Networks (EWSN'14). Oxford‚ UK. 2014.
Details about Poster: WiFi sensors meet visual tracking for an accurate positioning system | BibTeX data for Poster: WiFi sensors meet visual tracking for an accurate positioning system | Download EWSN14_Poster (003).pdf of Poster: WiFi sensors meet visual tracking for an accurate positioning system | Download ewsn14.pdf of Poster: WiFi sensors meet visual tracking for an accurate positioning system
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[64]
RadarLoc: Learning to Relocalize in FMCW Radar
Wei Wang Pedro P. B. de Gusmao Bo Yang Andrew Markham and Niki Trigoni
In IEEE International Conference on Robotics and Automation (ICRA). 2021.
Details about RadarLoc: Learning to Relocalize in FMCW Radar | BibTeX data for RadarLoc: Learning to Relocalize in FMCW Radar | Download (pdf) of RadarLoc: Learning to Relocalize in FMCW Radar
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[65]
RandLA−Net: Efficient Semantic Segmentation of Large−Scale Point Clouds
Qingyong Hu‚ Bo Yang‚ Linhai Xie‚ Stefano Rosa‚ Yulan Guo‚ Zhihua Wang‚ Niki Trigoni and Andrew Markham
In IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR Oral). 2020.
Details about RandLA−Net: Efficient Semantic Segmentation of Large−Scale Point Clouds | BibTeX data for RandLA−Net: Efficient Semantic Segmentation of Large−Scale Point Clouds | Download (pdf) of RandLA−Net: Efficient Semantic Segmentation of Large−Scale Point Clouds | Link to RandLA−Net: Efficient Semantic Segmentation of Large−Scale Point Clouds
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[66]
Revealing the hidden lives of underground animals using magneto−inductive tracking
Andrew Markham‚ Niki Trigoni‚ Stephen A. Ellwood and David W. Macdonald
In 8th ACM Conference on Embedded Networked Sensor Systems (Sensys 2010). Zurich‚ Switzerland. November, 2010.
Details about Revealing the hidden lives of underground animals using magneto−inductive tracking | BibTeX data for Revealing the hidden lives of underground animals using magneto−inductive tracking | Download (pdf) of Revealing the hidden lives of underground animals using magneto−inductive tracking
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[67]
Robust Attentional Aggregation of Deep Feature Sets for Multi−view 3D Reconstruction
Bo Yang‚ Sen Wang‚ Andrew Markham and Niki Trigoni
In International Journal of Computer Vision (IJCV). 2019.
Details about Robust Attentional Aggregation of Deep Feature Sets for Multi−view 3D Reconstruction | BibTeX data for Robust Attentional Aggregation of Deep Feature Sets for Multi−view 3D Reconstruction | Download (pdf) of Robust Attentional Aggregation of Deep Feature Sets for Multi−view 3D Reconstruction | DOI (10.1007/s11263-019-01217-w)
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[68]
Robust Indoor Positioning with Lifelong Learning
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In IEEE Journal on Selected Areas in Communications. Vol. PP. No. 99. Pages PP. 2015.
Details about Robust Indoor Positioning with Lifelong Learning | BibTeX data for Robust Indoor Positioning with Lifelong Learning | Download (pdf) of Robust Indoor Positioning with Lifelong Learning
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[69]
Robust pedestrian dead reckoning (R−PDR) for arbitrary mobile device placement
Zhuoling Xiao‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In The 5th International Conference on Indoor Positioning and Indoor Navigation. Busan‚ Korea. 2014.
Details about Robust pedestrian dead reckoning (R−PDR) for arbitrary mobile device placement | BibTeX data for Robust pedestrian dead reckoning (R−PDR) for arbitrary mobile device placement | Link to Robust pedestrian dead reckoning (R−PDR) for arbitrary mobile device placement
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[70]
Robust vision−based indoor localization
Ronald Clark‚ Niki Trigoni and Andrew Markham
In Proceedings of the 14th international conference on information processing in sensor networks (IPSN) − poster paper. 2015.
Details about Robust vision−based indoor localization | BibTeX data for Robust vision−based indoor localization
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[71]
SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data
Chris Xiaoxuan Lu‚ Hongkai Wen‚ Sen Wang‚ Andrew Markham and Niki Trigoni
In ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 2017.
Details about SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data | BibTeX data for SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data | Download (pdf) of SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data
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[72]
See Through Smoke: Robust Indoor Mapping with Low−cost mmWave Radar
Chris Xiaoxuan Lu‚ Stefano Rosa‚ Peijun Zhao‚ Bing Wang‚ Changhao Chen‚ John Stankovic‚ Niki Trigoni and Andrew Markham
In ACM International Conference on Mobile Systems‚ Applications‚ and Services (MobiSys). 2020.
Details about See Through Smoke: Robust Indoor Mapping with Low−cost mmWave Radar | BibTeX data for See Through Smoke: Robust Indoor Mapping with Low−cost mmWave Radar | Download (pdf) of See Through Smoke: Robust Indoor Mapping with Low−cost mmWave Radar
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[73]
Selective Sensor Fusion for Neural Visual Inertial Odometry
Changhao Chen‚ Stefano Rosa‚ Yishu Miao‚ Chris Xiaoxuan Lu‚ Wei Wu‚ Andrew Markham and Niki Trigoni
In Conference on Computer Vision and Pattern Recognition (CVPR−19). 2019.
Details about Selective Sensor Fusion for Neural Visual Inertial Odometry | BibTeX data for Selective Sensor Fusion for Neural Visual Inertial Odometry | Download (pdf) of Selective Sensor Fusion for Neural Visual Inertial Odometry
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[74]
Sensor Fusion for Magneto−Inductive Navigation
Johan Wahlström Manon Kok Pedro Porto Buarque de Gusmsao Traian E. Abrudan Niki Trigoni and Andrew Markham
In IEEE Sensors Journal. 2019.
Details about Sensor Fusion for Magneto−Inductive Navigation | BibTeX data for Sensor Fusion for Magneto−Inductive Navigation | DOI (10.1109/JSEN.2019.2942451) | Link to Sensor Fusion for Magneto−Inductive Navigation
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[75]
SnapNav: Learning Mapless Visual Navigation with Sparse Directional Guidance and Visual Reference
Linhai Xie‚ Andrew Markham and Niki Trigoni
In Robotics and Automation (ICRA)‚ 2020 IEEE/RSJ International Conference on. IEEE. 2020.
accepted
Details about SnapNav: Learning Mapless Visual Navigation with Sparse Directional Guidance and Visual Reference | BibTeX data for SnapNav: Learning Mapless Visual Navigation with Sparse Directional Guidance and Visual Reference | Download (pdf) of SnapNav: Learning Mapless Visual Navigation with Sparse Directional Guidance and Visual Reference
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[76]
Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning
Chris Xiaoxuan Lu‚ Bowen Du‚ Hongkai Wen‚ Sen Wang‚ Andrew Markham‚ Ivan Martinovic‚ Yiran Shen and Niki Trigoni
In ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp). 2018.
Details about Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning | BibTeX data for Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning | Download slides.key of Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning | Download [UbiComp2018]snoopy.pdf of Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning
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[77]
SoundDet: Polyphonic Sound Event Detection and Localization from Raw Waveform
N. Trigoni Y. He and A. Markham
In International Conference on Machine Learning. 2021.
Details about SoundDet: Polyphonic Sound Event Detection and Localization from Raw Waveform | BibTeX data for SoundDet: Polyphonic Sound Event Detection and Localization from Raw Waveform
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[78]
The Adaptive Social Hierarchy: A self organizing network based on naturally occurring structures
A. C. Markham and A. J. Wilkinson
In 1st International Conference on Bio Inspired mOdels of NEtwork‚ Information and Computing Systems (BIONETICS). 2006.
Details about The Adaptive Social Hierarchy: A self organizing network based on naturally occurring structures | BibTeX data for The Adaptive Social Hierarchy: A self organizing network based on naturally occurring structures | Download (pdf) of The Adaptive Social Hierarchy: A self organizing network based on naturally occurring structures
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[79]
The automatic evolution of distributed controllers to configure sensor network operation
Andrew Markham and Niki Trigoni
In The Computer Journal. March, 2010.
Details about The automatic evolution of distributed controllers to configure sensor network operation | BibTeX data for The automatic evolution of distributed controllers to configure sensor network operation | DOI (10.1093/comjnl/bxq016) | Link to The automatic evolution of distributed controllers to configure sensor network operation
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[80]
Title: Cut‚ Distil and Encode (CDE): Split Cloud−Edge Deep Inference
N. Trigoni M. Sbai M.R.U. Saputra and A. Markham
In IEEE International Conference on Sensing‚ Communication and Networking (SECON). 2021.
Details about Title: Cut‚ Distil and Encode (CDE): Split Cloud−Edge Deep Inference | BibTeX data for Title: Cut‚ Distil and Encode (CDE): Split Cloud−Edge Deep Inference
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[81]
Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning
Linhai Xie‚ Sen Wang‚ Andrew Markham and Niki Trigoni
In RSS 2017 workshop on New Frontiers for Deep Learning in Robotics. 2017.
Details about Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning | BibTeX data for Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning | Download (pdf) of Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning
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[82]
Tracking People in Highly Dynamic Industrial Environments
S. Papaioannou‚ A. Markham and N. Trigoni
In IEEE Transactions on Mobile Computing (Issue: 99). 2016.
Details about Tracking People in Highly Dynamic Industrial Environments | BibTeX data for Tracking People in Highly Dynamic Industrial Environments | Download (pdf) of Tracking People in Highly Dynamic Industrial Environments
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[83]
Transferring Physical Motion Between Domains for Neural Inertial Tracking
Changhao Chen‚ Yishu Miao‚ Chris Xiaoxuan Lu‚ Phil Blunsom‚ Andrew Markham and Niki Trigoni
In NIPS 2018 workshop on Modelling the Physical world: Perception‚ Learning and Control. 2018.
Details about Transferring Physical Motion Between Domains for Neural Inertial Tracking | BibTeX data for Transferring Physical Motion Between Domains for Neural Inertial Tracking | Download (pdf) of Transferring Physical Motion Between Domains for Neural Inertial Tracking
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[84]
Underground Incrementally Deployed Magneto−Inductive 3−D Positioning Network
T. Abrudan‚ Z. Xiao‚ A. Markham and N. Trigoni
In IEEE Transactions on Geoscience and Remote Sensing 54(8). Pages 4376−4391. 2016.
Details about Underground Incrementally Deployed Magneto−Inductive 3−D Positioning Network | BibTeX data for Underground Incrementally Deployed Magneto−Inductive 3−D Positioning Network | Download (pdf) of Underground Incrementally Deployed Magneto−Inductive 3−D Positioning Network
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[85]
Underground Localization in 3−D Using Magneto−Inductive Tracking
Andrew Markham and Niki Trigoni
In IEEE Sensors Journal. Vol. 12. No. 6. Pages 1809–1816. June, 2012.
Details about Underground Localization in 3−D Using Magneto−Inductive Tracking | BibTeX data for Underground Localization in 3−D Using Magneto−Inductive Tracking | DOI (10.1109/JSEN.2011.2178064) | Link to Underground Localization in 3−D Using Magneto−Inductive Tracking
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[86]
VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem
R. Clark‚ S. Wang‚ H. Wen‚ A. Markham and N. Trigoni
In AAAI Conference on Artificial Intelligence (AAAI). 2017.
Details about VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem | BibTeX data for VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem | Download (pdf) of VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem
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[87]
VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization
Kaichen Zhou Changhao Chen Bing Wang Muhamad Risqi U. Saputra Niki Trigoni and Andrew Markham
In AAAI Conference on Artificial Intelligence (AAAI). 2021.
Details about VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization | BibTeX data for VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization | Download (pdf) of VMLoc: Variational Fusion For Learning−Based Multimodal Camera Localization
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[88]
VeriNet: User Verification on Smartwatches via Behavior Biometrics
Chris Xiaoxuan Lu‚ Bowen Du‚ Xuan Kan‚ Hongkai Wen‚ Andrew Markham and Niki Trigoni
In ACM Sensys Workshop on Mobile Crowdsensing Systems and Applications. 2017.
Details about VeriNet: User Verification on Smartwatches via Behavior Biometrics | BibTeX data for VeriNet: User Verification on Smartwatches via Behavior Biometrics | Download (pdf) of VeriNet: User Verification on Smartwatches via Behavior Biometrics
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[89]
VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization
Ronald Clark‚ Sen Wang‚ Andrew Markham‚ Niki Trigoni and Hongkai Wen
In Computer Vision and Pattern Recognition (CVPR). 2017.
Details about VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization | BibTeX data for VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization | Download (pdf) of VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization
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[90]
Visual SLAM and Structure from Motion in Dynamic Environments: A Survey
M. R. U. Saputra; A. Markham; and N. Trigoni
In ACM Computing Surveys (CSUR) 51 (2)‚ 37. 2018.
Details about Visual SLAM and Structure from Motion in Dynamic Environments: A Survey | BibTeX data for Visual SLAM and Structure from Motion in Dynamic Environments: A Survey | Download (pdf) of Visual SLAM and Structure from Motion in Dynamic Environments: A Survey
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[91]
WILDSENSING: Design and Deployment of a Sustainable Sensor Network for Wildlife Monitoring
V. Dyo‚ S. Ellwood‚ D. Macdonald‚ A. Markham‚ N. Trigoni‚ R. Wohlers‚ C. Mascolo‚ B. Pasztor‚ S. Scellato and K. Yousef
In ACM Transactions on Sensor Networks. 2012.
Details about WILDSENSING: Design and Deployment of a Sustainable Sensor Network for Wildlife Monitoring | BibTeX data for WILDSENSING: Design and Deployment of a Sustainable Sensor Network for Wildlife Monitoring | Download (pdf) of WILDSENSING: Design and Deployment of a Sustainable Sensor Network for Wildlife Monitoring
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[92]
Zero−Velocity Detection – A Bayesian Approach to Adaptive Thresholding
Johan Wahlström‚ Isaac Skog‚ Fredrik Gustafsson‚ Andrew Markham and Niki Trigoni
In IEEE Sensors Letters. 2019.
Details about Zero−Velocity Detection – A Bayesian Approach to Adaptive Thresholding | BibTeX data for Zero−Velocity Detection – A Bayesian Approach to Adaptive Thresholding | Link to Zero−Velocity Detection – A Bayesian Approach to Adaptive Thresholding
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[93]
iMag+: An Accurate and Rapidly Deployable Inertial Magneto−Inductive SLAM System
N. Trigoni B. Wei and A. Markham
In IEEE Transactions on Mobile Computing. 2021.
Details about iMag+: An Accurate and Rapidly Deployable Inertial Magneto−Inductive SLAM System | BibTeX data for iMag+: An Accurate and Rapidly Deployable Inertial Magneto−Inductive SLAM System
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[94]
iMag: Accurate and rapidly deployable inertial magneto−inductive localisation
N. Trigoni B. Wei and A.C. Markham
In IEEE Intl Conference on Robotics and Automation (ICRA). 2018.
Details about iMag: Accurate and rapidly deployable inertial magneto−inductive localisation | BibTeX data for iMag: Accurate and rapidly deployable inertial magneto−inductive localisation | Download (pdf) of iMag: Accurate and rapidly deployable inertial magneto−inductive localisation
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[95]
mID: Tracking and Identifying People with Millimeter Wave Radar
Peijun Zhao‚ Chris Xiaoxuan Lu‚ Jianan Wang‚ Changhao Chen‚ Wei Wang‚ Niki Trigoni and Andrew Markham
In International Conference on Distributed Computing in Sensor Systems (DCOSS). 2019.
Details about mID: Tracking and Identifying People with Millimeter Wave Radar | BibTeX data for mID: Tracking and Identifying People with Millimeter Wave Radar | Download (pdf) of mID: Tracking and Identifying People with Millimeter Wave Radar
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[96]
milliEgo: Single−chip mmWave Radar Aided Egomotion Estimation via Deep Sensor Fusion
C. X. Lu M. R. U. Saputra P. Zhao Y. Almalioglu P. P. B. d. Gusmao C. Chen K. Sun N. Trigoni and A. Markham
In ACM Conference on Embedded Networked Sensor Systems (SenSys). 2020.
Details about milliEgo: Single−chip mmWave Radar Aided Egomotion Estimation via Deep Sensor Fusion | BibTeX data for milliEgo: Single−chip mmWave Radar Aided Egomotion Estimation via Deep Sensor Fusion | Download (pdf) of milliEgo: Single−chip mmWave Radar Aided Egomotion Estimation via Deep Sensor Fusion
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[97]
mmPoint: Dense Human Point Cloud Generation from mmWave
Qian Xie‚ Qianyi Deng‚ Ta−Ying Cheng‚ Peijun Zhao‚ Amir Patel‚ Niki Trigoni and Andrew Markham
In British Machine Vision Conference (BMVC). 2023.
Details about mmPoint: Dense Human Point Cloud Generation from mmWave | BibTeX data for mmPoint: Dense Human Point Cloud Generation from mmWave | Download (pdf) of mmPoint: Dense Human Point Cloud Generation from mmWave