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D-Index & Metrics

Computer Science

D-Index
57
Citations
12088
World Ranking
3867
National Ranking
236

Overview

Andrew Markham is affiliated with the University of Oxford in the United Kingdom. Their research spans fields primarily within Computer Science and Engineering, focusing on subfields such as Computer Vision and Pattern Recognition, Aerospace Engineering, Signal Processing, Electrical and Electronic Engineering, and Computational Mechanics.

Their body of work encompasses numerous topics, including Robotics and Sensor-Based Localization, Advanced Vision and Imaging, Indoor and Outdoor Localization Technologies, 3D Shape Modeling and Analysis, 3D Surveying and Cultural Heritage, Advanced Image and Video Retrieval Techniques, and Speech and Audio Processing.

Some of Markham's recent publications include the following papers:

  • "Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations," 2023, published in Advances in Computational Mathematics
  • "Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling," 2021, published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "AtLoc: Attention Guided Camera Localization," 2020, published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Deep-Learning-Based Pedestrian Inertial Navigation: Methods, Data Set, and On-Device Inference," 2020, published in IEEE Internet of Things Journal
  • "Milli-RIO: Ego-Motion Estimation With Low-Cost Millimetre-Wave Radar," 2020, published in IEEE Sensors Journal

Markham frequently collaborates with other researchers. Frequent co-authors include:

  • Niki Trigoni
  • Chris Xiaoxuan Lu
  • Changhao Chen
  • Peijun Zhao
  • Qingyong Hu

Their publications are often found in key academic venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Neural Networks and Learning Systems
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Sensors Journal
  • SSRN Electronic Journal

Best Publications

  • RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

    Qingyong Hu;Bo Yang;Linhai Xie;Stefano Rosa

  • Visual SLAM and Structure from Motion in Dynamic Environments: A Survey

    Muhamad Risqi U. Saputra;Andrew Markham;Niki Trigoni

  • VINet: Visual-Inertial Odometry as a Sequence-to-Sequence Learning Problem

    Ronald Clark;Sen Wang;Hongkai Wen;Andrew Markham

  • SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

    Sheng Ao;Qingyong Hu;Bo Yang;Andrew Markham

  • IONet: Learning to Cure the Curse of Drift in Inertial Odometry

    Changhao Chen;Xiaoxuan Lu;Andrew Markham;Niki Trigoni

  • VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization

    Ronald Clark;Sen Wang;Andrew Markham;Niki Trigoni

  • Non-Line-of-Sight Identification and Mitigation Using Received Signal Strength

    Zhuoling Xiao;Hongkai Wen;Andrew Markham;Niki Trigoni

  • Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

    Bo Yang;Jianan Wang;Ronald Clark;Qingyong Hu

  • Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations.

    Ben Moseley;Andrew Markham;Tarje Nissen-Meyer

  • mID: Tracking and Identifying People with Millimeter Wave Radar

    Peijun Zhao;Chris Xiaoxuan Lu;Jianan Wang;Changhao Chen

  • Evolution and sustainability of a wildlife monitoring sensor network

    Vladimir Dyo;Stephen A. Ellwood;David W. Macdonald;Andrew Markham

  • GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

    Yasin Almalioglu;Muhamad Risqi U. Saputra;Pedro P. B. de Gusmao;Andrew Markham

  • Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges

    Qingyong Hu;Bo Yang;Sheikh Khalid;Wen Xiao

  • Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling.

    Qingyong Hu;Bo Yang;Linhai Xie;Stefano Rosa

  • 3D Object Reconstruction from a Single Depth View with Adversarial Learning

    Bo Yang;Hongkai Wen;Sen Wang;Ronald Clark

  • Does BTLE measure up against WiFi? A comparison of indoor location performance

    Xiaojie Zhao;Zhuoling Xiao;Andrew Markham;Niki Trigoni

  • SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds with 1000x Fewer Labels

    Unknown

  • Lightweight map matching for indoor localisation using conditional random fields

    Zhuoling Xiao;Hongkai Wen;Andrew Markham;Niki Trigoni

  • Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

    Linhai Xie;Sen Wang;Andrew Markham;Niki Trigoni

  • AtLoc: Attention Guided Camera Localization

    Bing Wang;Changhao Chen;Chris Xiaoxuan Lu;Peijun Zhao

  • See through smoke: robust indoor mapping with low-cost mmWave radar

    Chris Xiaoxuan Lu;Stefano Rosa;Peijun Zhao;Bing Wang

  • A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence

    Changhao Chen;Bing Wang;Chris Xiaoxuan Lu;Niki Trigoni

Frequent Co-Authors

Niki Trigoni
Niki Trigoni University of Oxford
Phil Blunsom
Phil Blunsom University of Oxford
Yulan Guo
Yulan Guo Sun Yat-sen University
Stephen J. Roberts
Stephen J. Roberts University of Oxford
John A. Stankovic
John A. Stankovic University of Virginia
Cecilia Mascolo
Cecilia Mascolo University of Cambridge
Ivan Martinovic
Ivan Martinovic University of Oxford
Fredrik Gustafsson
Fredrik Gustafsson Linköping University
Salvatore Scellato
Salvatore Scellato Google (United States)
Fritz Vollrath
Fritz Vollrath University of Oxford

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