Dong Sun Park

3.2k total citations · 1 hit paper
72 papers, 2.1k citations indexed

About

Dong Sun Park is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Plant Science. According to data from OpenAlex, Dong Sun Park has authored 72 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 22 papers in Signal Processing and 18 papers in Plant Science. Recurrent topics in Dong Sun Park's work include Biometric Identification and Security (19 papers), Smart Agriculture and AI (18 papers) and Face and Expression Recognition (12 papers). Dong Sun Park is often cited by papers focused on Biometric Identification and Security (19 papers), Smart Agriculture and AI (18 papers) and Face and Expression Recognition (12 papers). Dong Sun Park collaborates with scholars based in South Korea, China and United States. Dong Sun Park's co-authors include Sook Yoon, Alvaro Fuentes, Mingle Xu, Zhihui Wang, Yu Lu, Shan Juan Xie, Yong Yang, Jianwei Zhao, Shuying Huang and Nini Rao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Dong Sun Park

70 papers receiving 2.0k citations

Hit Papers

align trajectories

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.

A Comprehensive Survey of Image Augmentation Techniques for Deep Learning

2023 319 citations Mingle Xu, Sook Yoon et al. profile →

Peers

Dong Sun Park

CVPR

SP

AI

PS

GENET

Sook Yoon South Korea

Jian Hou China

Shuqiang Jiang China

Jucheng Yang China

Liu Liu China

Qijun Zhao China

Anand Singh Jalal India

Yu Sun China

Dexing Zhong China

D. S. Guru India

Sook Yoon South Korea

Dong Sun Park

606 ×0.8

CVPR

452 ×0.8

SP

268 ×0.6

AI

1.4k ×3.2

PS

241 ×1.0

GENET

Citations per year, relative to Dong Sun Park Dong Sun Park (= 1×) peers Sook Yoon

Countries citing papers authored by Dong Sun Park

Since Specialization

Citations

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

Fields of papers citing papers by Dong Sun Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong Sun Park. 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 Dong Sun Park. The network helps show where Dong Sun Park may publish in the future.

Co-authorship network of co-authors of Dong Sun Park

This figure shows the co-authorship network connecting the top 25 collaborators of Dong Sun Park. A scholar is included among the top collaborators of Dong Sun Park 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 Dong Sun Park. Dong Sun Park is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Fuentes, Alvaro, Sook Yoon, & Dong Sun Park. (2025). AI-Driven decisions for smarter, sustainable greenhouse vegetable production. International Journal of Vegetable Science. 32(1). 1–7.

2.

Fuentes, Alvaro, et al.. (2025). Comprehensive plant health monitoring: expert-level assessment with spatio-temporal image data. Frontiers in Plant Science. 16. 1511651–1511651.

3.

Fuentes, Alvaro, et al.. (2025). Harnessing prototype networks for novel plant species and disease classification in open-world scenarios. Engineering Applications of Artificial Intelligence. 156. 111016–111016. 2 indexed citations

4.

Chaudhary, Girdhari, et al.. (2025). Attention-Based Deep Neural Network for High-Dimensional Microwave Modeling of Non-Reciprocal Bandpass Filters. IEEE Access. 13. 56220–56236. 1 indexed citations

5.

Fuentes, Alvaro, et al.. (2025). Utilizing farm knowledge for indoor precision livestock farming: Time-domain adaptation of cattle face recognition. Computers and Electronics in Agriculture. 234. 110301–110301. 5 indexed citations

6.

Xu, Mingle, Jaehwan Lee, Sook Yoon, Hyongsuk Kim, & Dong Sun Park. (2024). Variation-aware semantic image synthesis. Image and Vision Computing. 142. 104914–104914. 1 indexed citations

7.

Fuentes, Alvaro, et al.. (2024). Visual information guided multi-modal model for plant disease anomaly detection. SHILAP Revista de lepidopterología. 9. 100568–100568. 5 indexed citations

8.

Meng, Yao, Mingle Xu, Hyongsuk Kim, et al.. (2023). Known and unknown class recognition on plant species and diseases. Computers and Electronics in Agriculture. 215. 108408–108408. 7 indexed citations

9.

Fuentes, Alvaro, et al.. (2023). Deep learning-based multi-cattle tracking in crowded livestock farming using video. Computers and Electronics in Agriculture. 212. 108044–108044. 33 indexed citations

10.

Fuentes, Alvaro, et al.. (2023). Multiview Monitoring of Individual Cattle Behavior Based on Action Recognition in Closed Barns Using Deep Learning. Animals. 13(12). 2020–2020. 27 indexed citations

11.

Fuentes, Alvaro, et al.. (2023). Local refinement mechanism for improved plant leaf segmentation in cluttered backgrounds. Frontiers in Plant Science. 14. 1211075–1211075. 4 indexed citations

12.

Xu, Mingle, Hyongsuk Kim, Jucheng Yang, et al.. (2023). Embracing limited and imperfect training datasets: opportunities and challenges in plant disease recognition using deep learning. Frontiers in Plant Science. 14. 1225409–1225409. 24 indexed citations

13.

Yoon, Sook, et al.. (2023). Improving Known–Unknown Cattle’s Face Recognition for Smart Livestock Farm Management. Animals. 13(22). 3588–3588. 16 indexed citations

14.

Xu, Mingle, Sook Yoon, Yongchae Jeong, & Dong Sun Park. (2022). Transfer learning for versatile plant disease recognition with limited data. Frontiers in Plant Science. 13. 1010981–1010981. 30 indexed citations

15.

Xu, Mingle, Sook Yoon, Alvaro Fuentes, Jucheng Yang, & Dong Sun Park. (2022). Style-Consistent Image Translation: A Novel Data Augmentation Paradigm to Improve Plant Disease Recognition. Frontiers in Plant Science. 12. 773142–773142. 40 indexed citations

16.

Fuentes, Alvaro, et al.. (2022). Multi-Cattle tracking with appearance and motion models in closed barns using deep learning. 11(8). 84–92. 1 indexed citations

17.

Fuentes, Alvaro, et al.. (2021). Open Set Self and Across Domain Adaptation for Tomato Disease Recognition With Deep Learning Techniques. Frontiers in Plant Science. 12. 758027–758027. 18 indexed citations

18.

Fuentes, Alvaro, Sook Yoon, Jae-Su Lee, & Dong Sun Park. (2018). High-Performance Deep Neural Network-Based Tomato Plant Diseases and Pests Diagnosis System With Refinement Filter Bank. Frontiers in Plant Science. 9. 1162–1162. 143 indexed citations

19.

Sarker, Md. Mostafa Kamal, Sook Yoon, John J. Lee, & Dong Sun Park. (2013). Novel License Plate Detection Method Based on Heuristic Energy. The Journal of Korean Institute of Communications and Information Sciences. 38C(12). 1114–1125. 4 indexed citations

20.

Park, Dong Sun, et al.. (2008). Fingerprint Verification Based on Invariant Moment Features and Nonlinear BPNN. International Journal of Control Automation and Systems. 6(6). 800–808. 31 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.

Explore authors with similar magnitude of impact