Ola Ringdahl

1.1k total citations · 1 hit paper
32 papers, 763 citations indexed

About

Ola Ringdahl is a scholar working on Plant Science, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Ola Ringdahl has authored 32 papers receiving a total of 763 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Plant Science, 11 papers in Computer Vision and Pattern Recognition and 11 papers in Mechanical Engineering. Recurrent topics in Ola Ringdahl's work include Smart Agriculture and AI (12 papers), Forest Biomass Utilization and Management (10 papers) and Robotic Path Planning Algorithms (9 papers). Ola Ringdahl is often cited by papers focused on Smart Agriculture and AI (12 papers), Forest Biomass Utilization and Management (10 papers) and Robotic Path Planning Algorithms (9 papers). Ola Ringdahl collaborates with scholars based in Sweden, Israel and Netherlands. Ola Ringdahl's co-authors include Thomas Hellström, Yael Edan, Polina Kurtser, Ola Lindroos, R. Barth, J. Hemming, Ohad Ben‐Shahar, Boaz Arad, J. Balendonck and Tomas Nordfjell and has published in prestigious journals such as Sensors, Remote Sensing and Canadian Journal of Forest Research.

In The Last Decade

Ola Ringdahl

31 papers receiving 707 citations

Hit Papers

Development of a sweet pepper harvesting robot 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ola Ringdahl Sweden 14 411 185 157 111 103 32 763
Scarlett Liu Australia 13 347 0.8× 120 0.6× 210 1.3× 42 0.4× 32 0.3× 24 779
Xinyu Xue China 18 894 2.2× 88 0.5× 70 0.4× 113 1.0× 38 0.4× 88 1.4k
Hak-Jin Kim South Korea 19 595 1.4× 99 0.5× 180 1.1× 95 0.9× 24 0.2× 100 1.3k
Dimitrios S. Paraforos Germany 20 706 1.7× 237 1.3× 257 1.6× 82 0.7× 31 0.3× 67 1.2k
Xiwen Luo China 21 857 2.1× 353 1.9× 119 0.8× 114 1.0× 19 0.2× 173 1.6k
Alessandro Biglia Italy 20 539 1.3× 169 0.9× 335 2.1× 71 0.6× 32 0.3× 49 1.2k
Kazunobu Ishii Japan 15 438 1.1× 139 0.8× 136 0.9× 133 1.2× 12 0.1× 69 823
Fiaz Ahmad Pakistan 18 368 0.9× 229 1.2× 70 0.4× 44 0.4× 26 0.3× 63 881
Pengchao Chen China 21 961 2.3× 139 0.8× 186 1.2× 51 0.5× 81 0.8× 56 1.3k
Luis Emmi Spain 16 581 1.4× 154 0.8× 83 0.5× 99 0.9× 14 0.1× 32 927

Countries citing papers authored by Ola Ringdahl

Since Specialization
Citations

This map shows the geographic impact of Ola Ringdahl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ola Ringdahl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ola Ringdahl more than expected).

Fields of papers citing papers by Ola Ringdahl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ola Ringdahl. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ola Ringdahl. The network helps show where Ola Ringdahl may publish in the future.

Co-authorship network of co-authors of Ola Ringdahl

This figure shows the co-authorship network connecting the top 25 collaborators of Ola Ringdahl. A scholar is included among the top collaborators of Ola Ringdahl based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ola Ringdahl. Ola Ringdahl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kurtser, Polina, et al.. (2020). PointNet and geometric reasoning for detection of grape vines from single frame RGB-D data in outdoor conditions. Örebro University Library (Örebro University). 1. 6–6. 5 indexed citations
2.
Arad, Boaz, J. Balendonck, R. Barth, et al.. (2020). Development of a sweet pepper harvesting robot. Journal of Field Robotics. 37(6). 1027–1039. 295 indexed citations breakdown →
3.
Kurtser, Polina, et al.. (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. 47 indexed citations
4.
Talbot, Bruce, et al.. (2019). Detection and Classification of Root and Butt-Rot (RBR) in Stumps of Norway Spruce Using RGB Images and Machine Learning. Sensors. 19(7). 1579–1579. 12 indexed citations
5.
Ringdahl, Ola, Polina Kurtser, & Yael Edan. (2018). Evaluation of approach strategies for harvesting robots: Case study of sweet pepper harvesting. Journal of Intelligent & Robotic Systems. 95(1). 149–164. 26 indexed citations
6.
Ringdahl, Ola, et al.. (2018). Adaptive Image Thresholding of Yellow Peppers for a Harvesting Robot. Robotics. 7(1). 11–11. 22 indexed citations
7.
Ringdahl, Ola, Polina Kurtser, R. Barth, & Yael Edan. (2016). Operational flow of an autonomous sweetpepper harvesting robot. Socio-Environmental Systems Modeling. 3 indexed citations
8.
Lindroos, Ola, et al.. (2015). Estimating the position of the harvester head : a key step towards the precision forestry of the future?. Croatian journal of forest engineering. 36(2). 147–164. 42 indexed citations
9.
Bontsema, J., Ola Ringdahl, R. Oberti, et al.. (2015). CROPS: Clever Robots for Crops. Socio-Environmental Systems Modeling. 21 indexed citations
10.
Barth, R., Thomas Buschmann, Yael Edan, et al.. (2014). Using ROS for Agricultural Robotics - Design Considerations and Experiences. Socio-Environmental Systems Modeling. 509–518. 13 indexed citations
11.
Hellström, Thomas & Ola Ringdahl. (2013). A software framework for agricultural and forestry robots. Industrial Robot the international journal of robotics research and application. 40(1). 20–26. 13 indexed citations
12.
Hellström, Thomas & Ola Ringdahl. (2012). A software framework for agricultural and forestry robotics. DiVA at Umeå University (Umeå University). 171–176. 1 indexed citations
13.
Ringdahl, Ola, Thomas Hellström, & Ola Lindroos. (2012). Potentials of possible machine systems for directly loading logs in cut-to-length harvesting. Canadian Journal of Forest Research. 42(5). 970–985. 21 indexed citations
14.
Ringdahl, Ola, Thomas Hellström, Iwan Wästerlund, & Ola Lindroos. (2012). Estimating wheel slip for a forest machine using RTK-DGPS. Journal of Terramechanics. 49(5). 271–279. 21 indexed citations
15.
Ringdahl, Ola, Ola Lindroos, Thomas Hellström, et al.. (2011). Path tracking in forest terrain by an autonomous forwarder. Scandinavian Journal of Forest Research. 26(4). 350–359. 27 indexed citations
16.
Athanassiadis, Dimitris, Dan Bergström, Thomas Hellström, et al.. (2010). PATH TRACKING FOR AUTONOMOUS FORWARDERS IN FOREST TERRAIN. Epsilon Open Archive (Sveriges lantbruksuniversitet biblioteket (Swedish University of Agricultural Sciences)). 42–43. 1 indexed citations
17.
Hellström, Thomas, et al.. (2009). Autonomous Forest Vehicles: Historic, envisioned, and state-of-the-art. International Journal of Forest Engineering. 20(1). 31–38. 50 indexed citations
18.
Ringdahl, Ola & Thomas Hellström. (2008). Autonomous Forest Machines: Techniques and Algorithms for Unmanned Vehicles. 3 indexed citations
19.
Hellström, Thomas, et al.. (2008). Autonomous forest machines : Past present and future. DiVA at Umeå University (Umeå University). 4 indexed citations
20.
Ringdahl, Ola. (1952). Catalogus Insectorum Sueciae. XI. Diptera Cyclorrapha: Muscaria Schizometopa.. 17. 129–186. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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