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Stephanie Lowry

Position: Associate Senior Lecturer School/office: School of Science and Technology

Email: c3RlcGhhbmllLmxvd3J5O29ydS5zZQ==

Phone: No number available

Room: T1221

Research subject

Computer Science

Research environments

Centre for Applied Autonomous Sensor Systems (AASS)

About Stephanie Lowry

I am an Assistant Professor in Computer Science at the Center for Applied Autonomous Sensor Systems (AASS). My research interests focus on how robots and other autonomous systems recognise and understand the world around them using visual perception.

My position is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP) research program.

Active projects

Completed projects

Semantic Robots

Research groups

Machine Perception and Interaction Lab

Publications

Articles in journals | Articles, reviews/surveys | Conference papers |

Articles in journals

Norinder, U. & Lowry, S. (2023). Predicting Larch Casebearer damage with confidence using Yolo network models and conformal prediction. Remote Sensing Letters, 14 (10), 1023-1035. [BibTeX]
Andreasson, H. , Larsson, J. & Lowry, S. (2022). A Local Planner for Accurate Positioning for a Multiple Steer-and-Drive Unit Vehicle Using Non-Linear Optimization. Sensors, 22 (7). [BibTeX]
Lowry, S. & Andreasson, H. (2018). Lightweight, Viewpoint-Invariant Visual Place Recognition in Changing Environments. IEEE Robotics and Automation Letters, 3 (2), 957-964. [BibTeX]
Lowry, S. & Milford, M. (2016). Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments. IEEE Transactions on robotics, 32 (3), 600-613. [BibTeX]
Lowry, S. , Sunderhauf, N. , Newman, P. , Leonard, J. , Cox, D. , Corke, P. & Milford, M. (2016). Visual Place Recognition: A Survey. IEEE Transactions on robotics, 32 (1), 1-19. [BibTeX]
Chen, Z. , Lowry, S. , Jacobson, A. , Hasselmo, M. E. & Milford, M. (2015). Bio-inspired homogeneous multi-scale place recognition. Neural Networks, 72, 48-61. [BibTeX]

Articles, reviews/surveys

Kurtser, P. & Lowry, S. (2023). RGB-D datasets for robotic perception in site-specific agricultural operations: A survey. Computers and Electronics in Agriculture, 212. [BibTeX]

Conference papers

Kucner, T. P. , Luperto, M. , Lowry, S. , Magnusson, M. & Lilienthal, A. (2021). Robust Frequency-Based Structure Extraction. In: 2021 IEEE International Conference on Robotics and Automation (ICRA). Paper presented at IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 30 - June 5, 2021. (pp. 1715-1721). IEEE. [BibTeX]
Adolfsson, D. , Lowry, S. , Magnusson, M. , Lilienthal, A. J. & Andreasson, H. (2019). A Submap per Perspective: Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality. In: 2019 European Conference on Mobile Robots (ECMR). Paper presented at European Conference on Mobile Robotics (ECMR), Prague, Czech Republic, September 4-6, 2019. IEEE. [BibTeX]
Lowry, S. (2019). Similarity criteria: evaluating perceptual change for visual localization. In: 2019 European Conference on Mobile Robots (ECMR). Paper presented at ECMR 2019 : 9th European Conference on Mobile Robots, Prague, Czech Republic, September 4-6, 2019. IEEE. [BibTeX]
Adolfsson, D. , Lowry, S. & Andreasson, H. (2018). Improving Localisation Accuracy using Submaps in warehouses. Paper presented at IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Workshop on Robotics for Logistics in Warehouses and Environments Shared with Humans, Madrid, Spain, October 5, 2018. [BibTeX]
Lowry, S. & Andreasson, H. (2018). LOGOS: Local geometric support for high-outlier spatial verification. Paper presented at IEEE International Conference of Robotics and Automation (ICRA 2018), Brisbane, Australia, May 21-25, 2018. (pp. 7262-7269). IEEE Computer Society. [BibTeX]
Lowry, S. & Andreasson, H. (2016). Visual place recognition techniques for pose estimation in changing environments. In: Visual Place Recognition: What is it Good For? workshop, Robotics Science and Systems (RSS) 2016. Paper presented at Visual Place Recognition: What is it Good For? workshop, Robotics: Science and Systems (RSS) 2016, Ann Arbor, MI, USA, 19 June, 2016. [BibTeX]
Lowry, S. & Milford, M. (2015). Building Beliefs: Unsupervised Generation of Observation Likelihoods for Probabilistic Localization in Changing Environments. In: IEEE International Conference on Intelligent Robots and Systems (IROS), IEEE, 2015. Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany, 29 Sep - 2 Oct, 2015. (pp. 3071-3078). New York, USA: IEEE. [BibTeX]
Chen, Z. , Lowry, S. , Jacobson, A. , Ge, Z. & Milford, M. (2015). Distance metric learning for feature-agnostic place recognition. In: Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Paper presented at 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 28 - October 2, 2015. (pp. 2556-2563). IEEE. [BibTeX]
Milford, M. , Shen, C. , Lowry, S. , Sünderhauf, N. , Shirazi, S. , Lin, G. , Liu, F. , Pepperell, E. & et al. (2015). Sequence Searching With Deep-Learnt Depth for Condition- and Viewpoint-Invariant Route-Based Place Recognition. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops. Paper presented at 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Boston, MA, USA, June 7-12, 2015. (pp. 18-25). IEEE conference proceedings. [BibTeX]