Chang‐Su Kim

311 papers receiving 6.2k citations

Hit Papers

Contrast Enhancement Based on Layered Difference Represen...201320262017202120132013200400600

Peers

Chang‐Su Kim
Comparison fields: 5 of 183
  • Computer Vision and Pattern Recognition 5.2k
  • Media Technology 1.3k
  • Signal Processing 789
  • Computer Graphics and Computer-Aided Design 491
  • Computational Mechanics 341
Replace Xiaonan Luo with:
Xiaonan Luo China
Mingli Song China
Ying Shan China
Siwei Ma China
Ge Li China
Tae‐Kyun Kim United Kingdom
Yong Xu China
Wenjun Zhang China
Mohammad Norouzi United States
Mao Ye China
Chang‐Su Kim relative to Xiaonan Luo China Xiaonan Luo's profile →
Citations per field
00.5×2.7×
Xiaonan Luo · 1×
Citations per year

Countries citing papers authored by Chang‐Su Kim

Since Specialization
Citations

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

Fields of papers citing papers by Chang‐Su Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chang‐Su Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Chang‐Su Kim. A scholar is included among the top collaborators of Chang‐Su 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 Chang‐Su Kim. Chang‐Su 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
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Order Learning and Its Application to Age Estimation
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6 4
7 12
8 5
9 17
10 77
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Contrast Enhancement Based on Layered Difference Representation of 2D Histogramsbreakdown →
675
12
Real-time acquisition and representation of 3D environmental data
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Viewing angle dependent coding of digital holograms
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14
SMIL Authoring System for Multimedia Object Presentation
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15
Design of Hybrid Network Probe Intrusion Detector using FCM
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A Study on Information Service System Satisfaction Survey
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Post-Processing Algorithm for Reducing Ringing Artefacts in Deblurred Images
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Empirical Study on the Ubiquitous Computing Characteristics Affecting the Use of U-Service
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Progressive coding of binary voxel models based on pattern code representation
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About Chang‐Su Kim

Chang‐Su Kim is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 355 papers that have together received 6.5k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (113 papers), Video Coding and Compression Technologies (65 papers) and Advanced Image Processing Techniques (53 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.2k citations), Media Technology (1.3k citations) and Computer Graphics and Computer-Aided Design (491 citations). Chang‐Su Kim has collaborated with scholars based in South Korea, United States and Hong Kong. Frequent co-authors include Chul Lee, Jae-Young Sim, Chulwoo Lee, Won-Dong Jang, Jin Hwan Kim, C.‐C. Jay Kuo, Yeong Jun Koh, Jae-Han Lee, Jingliang Peng and Jong‐Woo Han. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Chemistry of Materials and Advanced Functional 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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