Andrew Markham : Publications

Book chapters

• [1]

  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

• [2]

  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

• [3]

  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

Journal papers

• [1]

  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

• [2]

  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

• [3]

  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

• [4]

  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

• [5]

  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

• [6]

  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

• [7]

  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

• [8]

  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

• [9]

  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

• [10]

  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

• [11]

  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

• [12]

  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

• [13]

  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

• [14]

  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

• [15]

  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

• [16]

  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

• [17]

  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

• [18]

  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

• [19]

  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)

• [20]

  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

• [21]

  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

• [22]

  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

• [23]

  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

• [24]

  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

• [25]

  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

• [26]

  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)

• [27]

  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

• [28]

  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

• [29]

  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

• [30]

  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

• [31]

  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)

• [32]

  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

• [33]

  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

• [34]

  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

• [35]

  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

• [36]

  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

• [37]

  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?

• [38]

  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

• [39]

  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

• [40]

  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)

• [41]

  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)

• [42]

  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

• [43]

  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

• [44]

  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

• [45]

  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

• [46]

  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

• [47]

  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

Conference papers

• [1]

  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

• [2]

  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

• [3]

  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

• [4]

  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

• [5]

  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

• [6]

  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

• [7]

  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

• [8]

  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

• [9]

  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

• [10]

  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

• [11]

  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

• [12]

  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

• [13]

  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

• [14]

  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

• [15]

  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

• [16]

  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

• [17]

  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

• [18]

  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

• [19]

  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

• [20]

  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

• [21]

  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

• [22]

  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

• [23]

  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

• [24]

  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

• [25]

  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

• [26]

  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

• [27]

  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

• [28]

  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

• [29]

  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

• [30]

  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)

• [31]

  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

• [32]

  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)

• [33]

  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

• [34]

  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

• [35]

  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

• [36]

  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

• [37]

  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

• [38]

  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

• [39]

  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

• [40]

  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

• [41]

  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

• [42]

  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

• [43]

  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

• [44]

  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

• [45]

  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

• [46]

  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

Theses

• [1]

  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