Jonghwan Mun

1.5k citations
22 papers · 844 · h-index 15

Impact in

Papers in

Jonghwan Mun

22 papers receiving 824 citations

Peers

Jonghwan Mun
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 511
  • Pharmaceutical Science 61
  • Artificial Intelligence 241
  • Public Health, Environmental and Occupational Health 84
  • Ophthalmology 21
Replace Andreas Bartschat with:
Andreas Bartschat Germany
Xiangzhou Wang China
Wenzhong Yan China
Xinyan Wang China
Kuan Zhang China
Hanhui Li China
Yakun Zhang China
Hang Su China
Vivek Maik India
Jonghwan Mun relative to Andreas Bartschat Germany Andreas Bartschat's profile →
Citations per field
00.5×12.2×
Andreas Bartschat · 1×
Citations per year

Countries citing papers authored by Jonghwan Mun

Since Specialization
Citations

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

Fields of papers citing papers by Jonghwan Mun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jonghwan Mun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonghwan Mun Line = papers co-authored together Jonghwan Mun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020198
2 2019101
3 201968
4 201761
5 202254
6 202351
7 202350
8
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization
201738
9 201633
10 202028
11 202428
12 202224
13 202422
14
Learning to Specialize with Knowledge Distillation for Visual Question Answering
201817
15 202215
16 202311
17 202310
18 20239
19 20198
20 20237

About Jonghwan Mun

Jonghwan Mun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Materials Chemistry and Public Health, Environmental and Occupational Health, having authored 22 papers that have together received 844 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (11 papers), Human Pose and Action Recognition (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Corneal Surgery and Treatments (4 papers), Advanced Neural Network Applications (3 papers), Ocular Surface and Contact Lens (3 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (511 citations), Pharmaceutical Science (61 citations), Artificial Intelligence (241 citations), Public Health, Environmental and Occupational Health (84 citations) and Ophthalmology (21 citations). Jonghwan Mun has collaborated with scholars based in South Korea, Germany and Japan. Frequent co-authors include Bohyung Han, Minsu Cho, Sei Kwang Hahn, Byungseok Roh, Junbum Cha, Zhou Ren, Linjie Yang, Ning Xu, Hyeonwoo Noh and Choun‐Ki Joo. Their work appears in journals such as RSC Advances, ACS Applied Materials & Interfaces, Nano Energy, Advanced Drug Delivery Reviews and ACS Applied Electronic Materials.

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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