
Lowry Stephanie
Assistant Professor
AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T1221
Phone +46 (0)19 30 13 51
stephanie.lowry@oru.se
Publications
[1] | U. Norinder and S. Lowry. Predicting Larch Casebearer damage with confidence using Yolo network models and conformal prediction. Remote Sensing Letters, 14(10):1023-1035, 2023 [ BibTeX | DiVA ] |
[2] | P. Kurtser and S. Lowry. RGB-D datasets for robotic perception in site-specific agricultural operations : A survey. Computers and Electronics in Agriculture, 212, 2023 [ BibTeX | DiVA ] |
[3] | H. Andreasson, J. Larsson and S. Lowry. A Local Planner for Accurate Positioning for a Multiple Steer-and-Drive Unit Vehicle Using Non-Linear Optimization. Sensors, 22(7), 2022 [ BibTeX | DiVA | PDF ] |
[4] | T. P. Kucner, M. Luperto, S. Lowry, M. Magnusson and A. Lilienthal. Robust Frequency-Based Structure Extraction. In 2021 IEEE International Conference on Robotics and Automation (ICRA), pages 1715-1721, 2021 [ BibTeX | DiVA | PDF ] |
[5] | D. Adolfsson, S. Lowry, M. Magnusson, A. J. Lilienthal and H. Andreasson. A Submap per Perspective : Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality. In 2019 European Conference on Mobile Robots (ECMR) 2019 [ BibTeX | DiVA | PDF ] |
[6] | S. Lowry. Similarity criteria : evaluating perceptual change for visual localization. In 2019 European Conference on Mobile Robots (ECMR) 2019 [ BibTeX | DiVA | PDF ] |
[7] | D. Adolfsson, S. Lowry and H. Andreasson. Improving Localisation Accuracy using Submaps in warehouses. 2018 [ BibTeX | DiVA | PDF ] |
[8] | S. Lowry and H. Andreasson. Lightweight, Viewpoint-Invariant Visual Place Recognition in Changing Environments. IEEE Robotics and Automation Letters, 3(2):957-964, 2018 [ BibTeX | DiVA ] |
[9] | S. Lowry and H. Andreasson. LOGOS : Local geometric support for high-outlier spatial verification. , pages 7262-7269, 2018 [ BibTeX | DiVA ] |
[10] | S. Lowry and M. Milford. Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments. IEEE Transactions on robotics, 32(3):600-613, 2016 [ BibTeX | DiVA ] |
[11] | S. Lowry, N. Sunderhauf, P. Newman, J. Leonard, D. Cox, P. Corke and M. Milford. Visual Place Recognition : A Survey. IEEE Transactions on robotics, 32(1):1-19, 2016 [ BibTeX | DiVA ] |
[12] | S. Lowry and H. Andreasson. 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 2016 [ BibTeX | DiVA | PDF ] |
[13] | Z. Chen, S. Lowry, A. Jacobson, M. E. Hasselmo and M. Milford. Bio-inspired homogeneous multi-scale place recognition. Neural Networks, 72:48-61, 2015 [ BibTeX | DiVA ] |
[14] | S. Lowry and M. Milford. 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, pages 3071-3078, 2015 [ BibTeX | DiVA ] |
[15] | Z. Chen, S. Lowry, A. Jacobson, Z. Ge and M. Milford. Distance metric learning for feature-agnostic place recognition. In Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2556-2563, 2015 [ BibTeX | DiVA ] |
[16] | M. Milford, C. Shen, S. Lowry, N. Sünderhauf, S. Shirazi, G. Lin, F. Liu, E. Pepperell, C. Cadena, B. Upcroft and I. Reid. 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, pages 18-25, 2015 [ BibTeX | DiVA ] |