Youngmoo E. Kim

3.3k citations
124 papers · 2.3k indexed · h-index 26

Impact in

Papers in

Youngmoo E. Kim

119 papers receiving 2.1k citations

Peers

Youngmoo E. Kim
Comparison fields: 5 of 122
  • Signal Processing 1.0k
  • Computer Vision and Pattern Recognition 768
  • Cognitive Neuroscience 611
  • Music 73
  • Human-Computer Interaction 96
Replace Mikko A. Uusitalo with:
Mikko A. Uusitalo Finland
Tapio Lokki Finland
Ramanathan Subramanian India
Brian F. G. Katz France
Faisal Mohd-Yasin Malaysia
Davide Rocchesso Italy
Giovanni Saggio Italy
Shangfei Wang China
Xinyu Jiang China
Mengjie Huang China
Youngmoo E. Kim relative to Mikko A. Uusitalo Finland Mikko A. Uusitalo's profile →
Citations per field
00.5×10×13.7×
Mikko A. Uusitalo · 1×
Citations per year

Countries citing papers authored by Youngmoo E. Kim

Since Specialization
Citations

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

Fields of papers citing papers by Youngmoo E. Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Youngmoo E. Kim, 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 Youngmoo E. Kim Line = papers co-authored together Youngmoo E. Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202036
2 20191
3 201821
4 201826
5 20173
6 201637
7 201648
8 20151
9 20152
10 201419
11 20145
12 201319
13 20122
14 201110
15 201160
16 201013
17 20095
18
Comparison of a Joint Iterative Method for Multiple Speaker Identification with Sequential Blind Source Separation and Speaker Identification
20081
19
Blind channel identification for speech dereverberation using l1-norm sparse learning
200727
20 200031

About Youngmoo E. Kim

Youngmoo E. Kim is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Music, Architecture and Cognitive Neuroscience, having authored 124 papers that have together received 2.3k indexed citations. Recurring topics across this work include Music Technology and Sound Studies (59 papers), Music and Audio Processing (58 papers), Speech and Audio Processing (35 papers), Advanced materials and composites (21 papers), Neuroscience and Music Perception (17 papers), Powder Metallurgy Techniques and Materials (12 papers), Injection Molding Process and Properties (7 papers) and Intermetallics and Advanced Alloy Properties (7 papers). The work is most often cited by research in Signal Processing (1.0k citations), Computer Vision and Pattern Recognition (768 citations), Cognitive Neuroscience (611 citations), Music (73 citations) and Human-Computer Interaction (96 citations). Youngmoo E. Kim has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Erik M. Schmidt, Douglas Turnbull, Eun‐Pyo Kim, Sung Ho Lee, Brandon G. Morton, Jeffrey J. Scott, Keith D. Martin, Hasan Ayaz, Raymond Migneco and Soon Hyung Hong. Their work appears in journals such as International Journal of Refractory Metals and Hard Materials, IEEE Multimedia, Journal of Alloys and Compounds, Powder Technology and Metals and Materials International.

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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