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Computer Science

D-Index
52
Citations
14052
World Ranking
5007
National Ranking
147

Overview

Michael Milford is affiliated with the Queensland University of Technology in Australia. Their research primarily focuses on robotics, sensor-based localization, and advanced image and video retrieval techniques. They have contributed extensively to the fields of engineering and computer science, with particular emphasis on subfields such as computer vision and pattern recognition, aerospace engineering, electrical and electronic engineering, artificial intelligence, and control and systems engineering.

Milford's work addresses numerous topics related to localization technologies both indoors and outdoors, neural network applications, video surveillance and tracking, memory and neural computing, and vision and imaging. Their research output includes publications in leading venues, reflecting a consistent presence in the robotics and automation community.

  • Semantics for Robotic Mapping, Perception and Interaction: A Survey (2020), Foundations and Trends in Robotics
  • CoHOG: A Light-Weight, Compute-Efficient, and Training-Free Visual Place Recognition Technique for Changing Environments (2020), IEEE Robotics and Automation Letters
  • A Survey on Terrain Traversability Analysis for Autonomous Ground Vehicles: Methods, Sensors, and Challenges (2022), Field Robotics
  • Event-Based Visual Place Recognition With Ensembles of Temporal Windows (2020), IEEE Robotics and Automation Letters
  • Delta Descriptors: Change-Based Place Representation for Robust Visual Localization (2020), IEEE Robotics and Automation Letters

Frequent collaborators with Milford include Shoaib Ehsan, Tobias Fischer, Klaus D. McDonald-Maier, Sourav Garg, and Bruno Ferrarini. This collaboration network highlights interdisciplinary partnerships across various fields related to robotics and computer vision.

Milford's research frequently appears in the following publication venues:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • IEEE Robotics & Automation Magazine
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • IEEE Transactions on Robotics

Their work covers a broad range of topics, including:

  • Robotics and Sensor-Based Localization
  • Advanced Image and Video Retrieval Techniques
  • Indoor and Outdoor Localization Technologies
  • Advanced Neural Network Applications
  • Video Surveillance and Tracking Methods
  • Advanced Memory and Neural Computing
  • Advanced Vision and Imaging

Michael Milford's research trajectory demonstrates an integration of advanced theoretical methodologies with practical applications in robotics and autonomous systems, particularly emphasizing visual place recognition, terrain analysis, and change detection within dynamic environments.

Best Publications

  • Visual Place Recognition: A Survey

    Stephanie Lowry;Niko Sunderhauf;Paul Newman;John J. Leonard

  • SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights

    Michael J. Milford;Gordon. F. Wyeth

  • On the performance of ConvNet features for place recognition

    Niko Sunderhauf;Sareh Shirazi;Feras Dayoub;Ben Upcroft

  • The limits and potentials of deep learning for robotics

    Niko Sünderhauf;Oliver Brock;Walter J. Scheirer;Raia Hadsell

  • RatSLAM: a hippocampal model for simultaneous localization and mapping

    M.J. Milford;G.F. Wyeth;D. Prasser

  • Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free

    Niko Suenderhauf;Sareh Shirazi;Adam Jacobson;Feras Dayoub

  • Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System

    M.J. Milford;G.F. Wyeth

  • Deep learning features at scale for visual place recognition

    Zetao Chen;Adam Jacobson;Niko Sunderhauf;Ben Upcroft

  • Persistent Navigation and Mapping using a Biologically Inspired SLAM System

    Michael Milford;Gordon Wyeth

  • QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM

    Lachlan Nicholson;Michael Milford;Niko Sunderhauf

  • Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition

    Stephen Hausler;Sourav Garg;Ming Xu;Michael Milford

  • FAB-MAP + RatSLAM: Appearance-based SLAM for multiple times of day

    Arren J. Glover;William P. Maddern;Michael J. Milford;Gordon F. Wyeth

  • Convolutional Neural Network-based Place Recognition

    Zetao Chen;Obadiah Lam;Adam Jacobson;Michael Milford

  • Meaningful maps with object-oriented semantic mapping

    Niko Sunderhauf;Trung T. Pham;Yasir Latif;Michael Milford

  • Towards vision-based deep reinforcement learning for robotic motion control

    Fangyi Zhang;Juergen Leitner;Michael Milford;Ben Upcroft

  • OpenFABMAP: An open source toolbox for appearance-based loop closure detection

    Arren Glover;William Maddern;Michael Warren;Stephanie Reid

  • On the Performance of ConvNet Features for Place Recognition

    Niko Sünderhauf;Feras Dayoub;Sareh Shirazi;Ben Upcroft

  • Vision-based place recognition: how low can you go?

    Michael Milford

  • Place categorization and semantic mapping on a mobile robot

    Niko Sunderhauf;Feras Dayoub;Sean McMahon;Ben Talbot

  • Where Is Your Place, Visual Place Recognition?

    Sourav Garg;Tobias Fischer;Michael Milford

  • All-environment visual place recognition with SMART

    Edward Pepperell;Peter I. Corke;Michael J. Milford

  • OpenRatSLAM: an open source brain-based SLAM system

    David Ball;Scott Heath;Janet Wiles;Gordon Wyeth

Frequent Co-Authors

Niko Sünderhauf
Niko Sünderhauf Queensland University of Technology
Peter Corke
Peter Corke Queensland University of Technology
Ben Upcroft
Ben Upcroft Queensland University of Technology
Ian Reid
Ian Reid University of Adelaide
Walter J. Scheirer
Walter J. Scheirer University of Notre Dame
Michael E. Hasselmo
Michael E. Hasselmo Boston University
David D. Cox
David D. Cox IBM (United States)
Raia Hadsell
Raia Hadsell DeepMind (United Kingdom)
Robert Mahony
Robert Mahony Australian National University
Chunhua Shen
Chunhua Shen Zhejiang University

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