Polina Kurtser
Tjänstetitel: Forskare Organisation: Institutionen för naturvetenskap och teknikTelefon: 019 301410
Rum: T1213

Forskningsprojekt
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Avslutade projekt
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Publikationer
Artiklar i tidskrifter |
Konferensbidrag |
Artiklar i tidskrifter
- Kurtser, P. , Castro Alves, V. , Arunachalam, A. , Sjöberg, V. , Hanell, U. , Hyötyläinen, T. & Andreasson, H. (2021). Development of novel robotic platforms for mechanical stress induction, and their effects on plant morphology, elements, and metabolism. Scientific Reports, 11 (1).
- Herck, L. v. , Kurtser, P. , Wittemans, L. & Edan, Y. (2020). Crop design for improved robotic harvesting: A case study of sweet pepper harvesting. Biosystems Engineering, 192, 294-308.
- Arad, B. , Balendonck, J. , Barth, R. , Ben-Shahar, O. , Edan, Y. , Hellström, T. , Hemming, J. , Kurtser, P.
& et al.
(2020). Development of a sweet pepper harvesting robot. Journal of Field Robotics, 37 (6), 1027-1039.
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- Kurtser, P. , Ringdahl, O. , Rotstein, N. , Berenstein, R. & Edan, Y. (2020). In-field grape cluster size assessment for vine yield estimation using a mobile robot and a consumer level RGB-D camera. IEEE Robotics and Automation Letters, 5 (2), 2031-2038.
- Kurtser, P. & Edan, Y. (2020). Planning the sequence of tasks for harvesting robots. Robotics and Autonomous Systems, 131.
- Zemmour, E. , Kurtser, P. & Edan, Y. (2019). Automatic Parameter Tuning for Adaptive Thresholding in Fruit Detection. Sensors, 19 (9).
- Arad, B. , Kurtser, P. , Barnea, E. , Harel, B. , Edan, Y. & Ben-Shahar, O. (2019). Controlled Lighting and Illumination-Independent Target Detection for Real-Time Cost-Efficient Applications. The Case Study of Sweet Pepper Robotic Harvesting. Sensors, 19 (6).
- Ringdahl, O. , Kurtser, P.
& Edan, Y. (2019). Evaluation of approach strategies for harvesting robots: Case study of sweet pepper harvesting. Journal of Intelligent and Robotic Systems, 95 (1), 149-164.
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- Levi-Bliech, M. , Kurtser, P. , Pliskin, N. & Fink, L. (2019). Mobile apps and employee behavior: An empirical investigation of the implementation of a fleet-management app. International Journal of Information Management, 49, 355-365.
- Kurtser, P. & Edan, Y. (2018). Statistical models for fruit detectability: spatial and temporal analyses of sweet peppers. Biosystems Engineering, 171, 272-289.
- Kurtser, P. & Edan, Y. (2018). The use of dynamic sensing strategies to improve detection for a pepper harvesting robot. IEEE International Conference on Intelligent Robots and Systems. Proceedings, 8286-8293.
Konferensbidrag
- Kurtser, P. , Ringdahl, O. , Rotstein, N.
& Andreasson, H. (2020). PointNet and geometric reasoning for detection of grape vines from single frame RGB-D data in outdoor conditions.
I:
Proceedings of the Northern Lights Deep Learning Workshop. Konferensbidrag vid 3rd Northern Lights Deep Learning Workshop, Tromsö, Norway 20-21 January, 2019 (ss. 1-6). NLDL.
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- Kurtser, P. , Hanell, U. & Andreasson, H. (2020). Robotic Platform for Precise Mechanical Stress Induction in Greenhouses Cultivation. I: 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE). Konferensbidrag vid IEEE 16th International Conference on Automation Science and Engineering (CASE), (Online Zoom Meeting), Hong Kong, August 20-21, 2020 (ss. 1558-1565). IEEE.
- Ringdahl, O. , Kurtser, P. & Edan, Y. (2019). Performance of RGB-D camera for different object types in greenhouse conditions. I: Libor Přeučil, Sven Behnke, Miroslav Kulich, 2019 European Conference on Mobile Robots (ECMR). Konferensbidrag vid 2019 European Conference on Mobile Robots (ECMR), Prague, Czech Republic, September 4-6, 2019 (ss. 1-6). IEEE.
- Levi-Bliech, M. , Kurtser, P. , Pliskin, N. & Fink, L. (2018). The effects of a fleet-management app on driver behavior. Konferensbidrag vid 26th European Conference on Information Systems (ECIS2018), Portsmouth, UK, June 26-28, 2018..
- Zemmour, E. , Kurtser, P. & Edan, Y. (2017). Dynamic thresholding algorithm for robotic apple detection. I: 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). Konferensbidrag vid IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC 2017), Coimbra, Portugal- April 26-28, 2017 (ss. 240-246). IEEE.
- Ringdahl, O. , Kurtser, P.
& Edan, Y. (2017). Strategies for selecting best approach direction for a sweet-pepper harvesting robot.
I:
Yang Gao, Saber Fallah, Yaochu Jin, Constantina Lekakou, Towards Autonomous Robotic Systems (Taros 2017). Konferensbidrag vid TAROS 2017: the 18th Towards Autonomous Robotic Systems (TAROS) Conference, University of Surrey, Guildford, UK, July 19–21, 2017 (ss. 516-525). Cham: Springer.
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- Ringdahl, O. , Kurtser, P. , Barth, R.
& Edan, Y. (2016). Operational flow of an autonomous sweetpepper harvesting robot.
Konferensbidrag vid The 5th Israeli Conference on Robotics 2016, Air Force Conference Center Hertzilya, Israel, 13-14 April, 2016.
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- Kurtser, P. , Arad, B. , Ben-Shahar, O. , van Bree, M. , Moonen, J. , van Tujil, B.
& Edan, Y. (2016). Robotic data acquisition of sweet pepper images for research and development.
Konferensbidrag vid The 5th Israeli Conference on Robotics 2016, Air Force Conference Center Hertzilya, Israel, 13-14 April, 2016.
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- Harel, B. , Kurtser, P. , van Herck, L. , Parmet, Y.
& Edan, Y. (2016). Sweet pepper maturity evaluation via multiple viewpoints color analyses.
Konferensbidrag vid CIGR-AgEng Conference, Aarhus, Denmark, 26-29 June, 2016 (ss. 1-7).
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- Kurtser, P. , Levi, O. & Gontar, V. (2012). Detection and classification of ECG chaotic components using ANN trained by specially simulated data. I: Jayne, C; Yue, S; Iliadis, L, Engineering Applications of Neural Networks. Konferensbidrag vid 13th International Conference on Engineering Applications of Neural Networks (EANN 2012), London, UK, September 20-23, 2012 (ss. 193-202). Berlin, Heidelberg: Springer.