Hyun Kim

2.7k citations
128 papers · 1.3k indexed · 1 hit paper · h-index 18
Topics
Advanced Neural Network Applications (53 papers)Domain Adaptation and Few-Shot Learning (19 papers)Parallel Computing and Optimization Techniques (19 papers)

In The Last Decade

Hyun Kim

107 papers receiving 1.3k citations

Hit Papers

A High-Throughput and Power-Efficient FPGA Implementation...20192026202120232019100200300

Peers

Hyun Kim
Comparison fields: 5 of 103
  • Computer Vision and Pattern Recognition 812
  • Electrical and Electronic Engineering 439
  • Artificial Intelligence 308
  • Hardware and Architecture 158
  • Computer Networks and Communications 133
Replace Yuhao Zhu with:
Yuhao Zhu United States
Caiwen Ding United States
Wei Niu United States
Bin Ren United States
Han Wang China
Haotong Qin China
Ming Liu China
Anjali Agarwal Canada
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Hyun Kim relative to Yuhao Zhu United States Yuhao Zhu's profile →
Citations per field
00.5×1.7×
Yuhao Zhu · 1×
Citations per year

Countries citing papers authored by Hyun Kim

Since Specialization
Citations

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

Fields of papers citing papers by Hyun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyun Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Hyun Kim. A scholar is included among the top collaborators of Hyun Kim 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 Hyun Kim. Hyun Kim 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
#WorkIndexed citations
1 0
2 0
3 10
4 2
5 0
6 1
7 4
8 0
9 5
10 5
11 4
12 35
13 1
14 34
15
A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detectionbreakdown →
323
16 7
17 4
18 4
19 6
20 24

About Hyun Kim

Hyun Kim is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Instrumentation, having authored 128 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (53 papers), Domain Adaptation and Few-Shot Learning (19 papers) and Parallel Computing and Optimization Techniques (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (812 citations), Hardware and Architecture (158 citations) and Media Technology (99 citations). Hyun Kim has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Hyuk‐Jae Lee, Duy Thanh Nguyen, Tuan Nghia Nguyen, Yeonho Lee, Dohyung Kim, Ik‐Joon Chang, Ji-Woong Choi, Moon-Soo Kim, Wooshik Kim and Chang-Joo Kim. Their work appears in journals such as PLoS ONE, Optics Express and IEEE Access.

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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