Yeongmin Ko

476 total citations
11 papers, 267 citations indexed

About

Yeongmin Ko is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Media Technology. According to data from OpenAlex, Yeongmin Ko has authored 11 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 4 papers in Aerospace Engineering and 3 papers in Media Technology. Recurrent topics in Yeongmin Ko's work include Advanced Neural Network Applications (5 papers), Robotics and Sensor-Based Localization (4 papers) and Advanced Image Processing Techniques (2 papers). Yeongmin Ko is often cited by papers focused on Advanced Neural Network Applications (5 papers), Robotics and Sensor-Based Localization (4 papers) and Advanced Image Processing Techniques (2 papers). Yeongmin Ko collaborates with scholars based in South Korea, Saudi Arabia and Canada. Yeongmin Ko's co-authors include Moongu Jeon, Younkwan Lee, Farzeen Munir, Shoaib Azam, Witold Pedrycz, Ahmad Muqeem Sheri, Juhyun Lee, Yong-Jun Jang, Hae‐Gon Jeon and Yechan Kim and has published in prestigious journals such as IEEE Transactions on Intelligent Transportation Systems, Information Fusion and 2022 International Conference on Robotics and Automation (ICRA).

In The Last Decade

Yeongmin Ko

11 papers receiving 256 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yeongmin Ko South Korea	6	202	175	58	54	39	11	267
Huai Yuan China	13	312 1.5×	162 0.9×	69 1.2×	44 0.8×	37 0.9×	31	373
Jon Arróspide Spain	11	326 1.6×	175 1.0×	73 1.3×	51 0.9×	31 0.8×	18	395
Joon Woong Lee South Korea	8	222 1.1×	217 1.2×	24 0.4×	51 0.9×	62 1.6×	13	314
Anselm Haselhoff Germany	9	161 0.8×	93 0.5×	24 0.4×	61 1.1×	22 0.6×	15	256
Gwenaëlle Toulminet France	9	294 1.5×	215 1.2×	39 0.7×	25 0.5×	29 0.7×	14	358
Manwen Liao Hong Kong	3	157 0.8×	105 0.6×	20 0.3×	34 0.6×	17 0.4×	5	238
Jakub Špaňhel Czechia	8	247 1.2×	84 0.5×	115 2.0×	41 0.8×	16 0.4×	17	315
Alexander Filonenko South Korea	11	297 1.5×	53 0.3×	24 0.4×	49 0.9×	29 0.7×	31	371
Stéphane Mousset France	9	265 1.3×	173 1.0×	34 0.6×	32 0.6×	13 0.3×	18	347
Noa Garnett Israel	4	223 1.1×	158 0.9×	28 0.5×	31 0.6×	56 1.4×	5	274

Countries citing papers authored by Yeongmin Ko

Since Specialization

Citations

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

Fields of papers citing papers by Yeongmin Ko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yeongmin Ko

This figure shows the co-authorship network connecting the top 25 collaborators of Yeongmin Ko. A scholar is included among the top collaborators of Yeongmin Ko 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 Yeongmin Ko. Yeongmin Ko 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:

11 of 11 papers shown

1.

Ko, Yeongmin, et al.. (2023). An Encoder-Sequencer-Decoder Network for Lane Detection to Facilitate Autonomous Driving. 899–904. 1 indexed citations

2.

Ko, Yeongmin, et al.. (2022). Spectral-invariant matching network. Information Fusion. 91. 623–632. 4 indexed citations

3.

Lee, Younkwan, Yeongmin Ko, Yechan Kim, & Moongu Jeon. (2022). Perception-Friendly Video Enhancement for Autonomous Driving under Adverse Weather Conditions. 2022 International Conference on Robotics and Automation (ICRA). 7760–7767. 2 indexed citations

4.

Ko, Yeongmin, Younkwan Lee, Shoaib Azam, et al.. (2021). Key Points Estimation and Point Instance Segmentation Approach for Lane Detection. IEEE Transactions on Intelligent Transportation Systems. 23(7). 8949–8958. 199 indexed citations

5.

Lee, Younkwan, et al.. (2021). Task-Driven Deep Image Enhancement Network for Autonomous Driving in Bad Weather. 13746–13753. 18 indexed citations

6.

Lee, Younkwan, et al.. (2021). License Plate Detection via Information Maximization. IEEE Transactions on Intelligent Transportation Systems. 23(9). 14908–14921. 9 indexed citations

7.

Azam, Shoaib, et al.. (2019). Data fusion of Lidar and Thermal Camera for Autonomous driving. T2A.5–T2A.5. 8 indexed citations

8.

Munir, Farzeen, Shoaib Azam, Ahmad Muqeem Sheri, Yeongmin Ko, & Moongu Jeon. (2019). Where Am I: Localization and 3D Maps for Autonomous Vehicles. 452–457. 5 indexed citations

9.

Lee, Younkwan, et al.. (2019). Unconstrained Road Marking Recognition with Generative Adversarial Networks. 1414–1419. 9 indexed citations

10.

Munir, Farzeen, Shoaib Azam, Ahmad Muqeem Sheri, Yeongmin Ko, & Moongu Jeon. (2019). Where Am I: Localization and 3D Maps for Autonomous Vehicles. 452–457. 3 indexed citations

11.

Azam, Shoaib, et al.. (2018). Object Modeling from 3D Point Cloud Data for Self-Driving Vehicles. 8694 lncs. 409–414. 9 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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