Gert Kootstra

3.3k total citations · 1 hit paper
88 papers, 2.2k citations indexed

About

Gert Kootstra is a scholar working on Plant Science, Computer Vision and Pattern Recognition and Ecology. According to data from OpenAlex, Gert Kootstra has authored 88 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Plant Science, 22 papers in Computer Vision and Pattern Recognition and 18 papers in Ecology. Recurrent topics in Gert Kootstra's work include Smart Agriculture and AI (35 papers), Robotics and Sensor-Based Localization (18 papers) and Remote Sensing in Agriculture (17 papers). Gert Kootstra is often cited by papers focused on Smart Agriculture and AI (35 papers), Robotics and Sensor-Based Localization (18 papers) and Remote Sensing in Agriculture (17 papers). Gert Kootstra collaborates with scholars based in Netherlands, Sweden and China. Gert Kootstra's co-authors include E.J. van Henten, Danica Kragić, Bart de Boer, H.J. van de Zedde, Arne Bilberg, Pieter M. Blok, Aalt D. J. van Dijk, Dick de Ridder, Willem Kruijer and Lambert Schomaker and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Frontiers in Plant Science.

In The Last Decade

Gert Kootstra

77 papers receiving 2.1k citations

Hit Papers

Current status and future challenges in implementing and ... 2021 2026 2022 2024 2021 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Current status and future challenges in implementing and upscaling vertical farming systems
    2021 333 citations S.H. van Delden, Malleshaiah SharathKumar et al. Nature Food profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gert Kootstra Netherlands 23 1.0k 394 299 264 250 88 2.2k
Fernando Auat Cheein Chile 28 1.1k 1.1× 545 1.4× 358 1.2× 311 1.2× 155 0.6× 171 3.2k
Yael Edan Israel 34 2.1k 2.1× 869 2.2× 291 1.0× 430 1.6× 331 1.3× 199 4.9k
Flavio Prieto Colombia 20 311 0.3× 322 0.8× 123 0.4× 179 0.7× 66 0.3× 139 1.5k
Chao Qu United States 17 407 0.4× 340 0.9× 144 0.5× 167 0.6× 60 0.2× 39 1.3k
Tomàs Pallejà Spain 20 497 0.5× 206 0.5× 253 0.8× 179 0.7× 65 0.3× 51 1.2k
Gustavo Pessin Brazil 27 391 0.4× 494 1.3× 123 0.4× 110 0.4× 57 0.2× 129 2.4k
Hyoung Il Son South Korea 23 554 0.6× 443 1.1× 98 0.3× 225 0.9× 123 0.5× 97 2.0k
Syed Ali Raza Zaidi United Kingdom 28 393 0.4× 162 0.4× 137 0.5× 294 1.1× 103 0.4× 124 3.4k
Wenbin Li China 29 412 0.4× 233 0.6× 65 0.2× 370 1.4× 64 0.3× 327 3.1k

Countries citing papers authored by Gert Kootstra

Since Specialization
Citations

This map shows the geographic impact of Gert Kootstra'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 Gert Kootstra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gert Kootstra more than expected).

Fields of papers citing papers by Gert Kootstra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gert Kootstra. 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 Gert Kootstra. The network helps show where Gert Kootstra may publish in the future.

Co-authorship network of co-authors of Gert Kootstra

This figure shows the co-authorship network connecting the top 25 collaborators of Gert Kootstra. A scholar is included among the top collaborators of Gert Kootstra 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 Gert Kootstra. Gert Kootstra 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.
Henten, E.J. van, et al.. (2025). Multiple object tracking with multi-view active vision to effectively find plant nodes in a cluttered tomato greenhouse. Computers and Electronics in Agriculture. 234. 110266–110266.
2.
Henten, E.J. van, et al.. (2025). SSL-NBV: A self-supervised-learning-based next-best-view algorithm for efficient 3D plant reconstruction by a robot. Computers and Electronics in Agriculture. 233. 110121–110121. 1 indexed citations
3.
Kootstra, Gert, et al.. (2025). Transformer-based similarity learning for re-identification of chickens. Smart Agricultural Technology. 11. 100945–100945.
4.
5.
Kootstra, Gert, et al.. (2025). Multi-stage image-based approach for fish detection and weight estimation. Biosystems Engineering. 257. 104239–104239.
6.
Henten, E.J. van, et al.. (2025). UAV-based path planning for efficient localization of non-uniformly distributed weeds using prior knowledge: A reinforcement-learning approach. Computers and Electronics in Agriculture. 237. 110651–110651.
7.
Bartholomeus, Harm, et al.. (2024). An automatic 3D tomato plant stemwork phenotyping pipeline at internode level based on tree quantitative structural modelling algorithm. Computers and Electronics in Agriculture. 227. 109607–109607. 2 indexed citations
8.
Henten, E.J. van, et al.. (2024). Stereo Vision for Plant Detection in Dense Scenes. Sensors. 24(6). 1942–1942. 3 indexed citations
9.
Henten, E.J. van, et al.. (2024). Gradient-based Local Next-best-view Planning for Improved Perception of Targeted Plant Nodes. Socio-Environmental Systems Modeling. 15854–15860. 5 indexed citations
10.
Tol, P.P.J. van der, et al.. (2024). Video-based automatic lameness detection of dairy cows using pose estimation and multiple locomotion traits. Computers and Electronics in Agriculture. 223. 109040–109040. 21 indexed citations
11.
Bartholomeus, Harm, et al.. (2023). 3D data-augmentation methods for semantic segmentation of tomato plant parts. Frontiers in Plant Science. 14. 1045545–1045545. 13 indexed citations
12.
Kootstra, Gert, et al.. (2023). An integrated end-to-end deep neural network for automated detection of discarded fish species and their weight estimation. ICES Journal of Marine Science. 80(7). 1911–1922. 6 indexed citations
13.
Henten, E.J. van, et al.. (2022). Improved Point-Cloud Segmentation for Plant Phenotyping Through Class-Dependent Sampling of Training Data to Battle Class Imbalance. Frontiers in Plant Science. 13. 838190–838190. 19 indexed citations
14.
Kootstra, Gert, et al.. (2022). Passive radio frequency identification and video tracking for the determination of location and movement of broilers. Poultry Science. 102(3). 102412–102412. 10 indexed citations
15.
Delden, S.H. van, Malleshaiah SharathKumar, Luuk Graamans, et al.. (2021). Current status and future challenges in implementing and upscaling vertical farming systems. Nature Food. 2(12). 944–956. 333 indexed citations breakdown →
16.
17.
Blok, Pieter M., et al.. (2020). The effect of data augmentation and network simplification on the image‐based detection of broccoli heads with Mask R‐CNN. Journal of Field Robotics. 38(1). 85–104. 42 indexed citations
18.
Kootstra, Gert, et al.. (2011). Classification of rigid and deformable objects using a novel tactile sensor. University of Southern Denmark Research Portal (University of Southern Denmark). 427–434. 42 indexed citations
19.
Kootstra, Gert. (2006). Bottom-up and Top-down Influences on Eye Movements. Data Archiving and Networked Services (DANS). 28(28). 2 indexed citations
20.
Kootstra, Gert, et al.. (2003). Brand management : a theoretical and practical approach. 88 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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