Seokil Hong

625 total citations
2 papers, 291 citations indexed

About

Seokil Hong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, Seokil Hong has authored 2 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 1 paper in Artificial Intelligence and 0 papers in Infectious Diseases. Recurrent topics in Seokil Hong's work include Advanced Vision and Imaging (1 paper), Image and Signal Denoising Methods (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Seokil Hong is often cited by papers focused on Advanced Vision and Imaging (1 paper), Image and Signal Denoising Methods (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Seokil Hong collaborates with scholars based in Switzerland and South Korea. Seokil Hong's co-authors include Sungyong Baik, Kyoung Mu Lee, Seungjun Nah, Gyeongsik Moon, Sanghyun Son and Radu Timofte and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Seokil Hong

2 papers receiving 280 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seokil Hong Switzerland	2	268	102	14	14	9	2	291
Assaf Shocher Israel	4	246 0.9×	101 1.0×	5 0.4×	7 0.5×	6 0.7×	6	275
Lean Fu China	5	255 1.0×	131 1.3×	7 0.5×	5 0.4×	12 1.3×	5	277
Sunil Jaiswal India	10	251 0.9×	104 1.0×	10 0.7×	10 0.7×	12 1.3×	35	293
Chew Lim Tan Singapore	8	305 1.1×	93 0.9×	11 0.8×	34 2.4×	5 0.6×	15	331
Meiguang Jin Switzerland	8	223 0.8×	85 0.8×	6 0.4×	8 0.6×	8 0.9×	14	242
Shuaiyi Huang China	5	193 0.7×	64 0.6×	9 0.6×	21 1.5×	4 0.4×	8	215
Zeyu Xiao China	9	198 0.7×	60 0.6×	10 0.7×	7 0.5×	10 1.1×	28	223
Miguel Granados Germany	5	225 0.8×	57 0.6×	8 0.6×	6 0.4×	13 1.4×	11	249
Liying Lu United States	4	214 0.8×	97 1.0×	15 1.1×	9 0.6×	8 0.9×	6	236
Nicola Asuni Italy	6	390 1.5×	130 1.3×	35 2.5×	8 0.6×	16 1.8×	6	420

Countries citing papers authored by Seokil Hong

Since Specialization

Citations

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

Fields of papers citing papers by Seokil Hong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seokil Hong

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

All Works

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2 of 2 papers shown

1.

Baik, Sungyong, et al.. (2021). Learning to Forget for Meta-Learning via Task-and-Layer-Wise Attenuation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(11). 7718–7730. 13 indexed citations

2.

Nah, Seungjun, Sungyong Baik, Seokil Hong, et al.. (2019). NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study. 1996–2005. 278 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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