Minjae Lee

565 citations
16 papers · 318 indexed · 1 hit paper · h-index 5
Topics
Advanced Neural Network Applications (3 papers)Speech Recognition and Synthesis (3 papers)Speech and Audio Processing (2 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Minjae Lee

13 papers receiving 308 citations

Hit Papers

In Defence of Metric Learning for Speaker Recognition2020202620222024202050100150200

Peers

Minjae Lee
Comparison fields: 5 of 48
  • Artificial Intelligence 224
  • Signal Processing 195
  • Computer Vision and Pattern Recognition 43
  • Computational Mechanics 41
  • Computer Graphics and Computer-Aided Design 25
Replace Quan Wang with:
Quan Wang China
Youssef Oualil Germany
Alexander Schmidt Germany
Yuval Nirkin Israel
Saurabh Singh United States
Tero Tolonen Russia
Virginia Estellers Switzerland
Yinglin Zheng China
Andrew Owens United States
Dongsuk Yook South Korea
Minjae Lee relative to Quan Wang China Quan Wang's profile →
Citations per field
00.5×1.5×2.5×
Quan Wang · 1×
Citations per year

Countries citing papers authored by Minjae Lee

Since Specialization
Citations

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

Fields of papers citing papers by Minjae Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minjae Lee

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 11
2 0
3 4
4 0
5 2
6 1
7 7
8 9
9 1
10 3
11
In Defence of Metric Learning for Speaker Recognitionbreakdown →
232
12 1
13 3
14 2
15 3
16 39

About Minjae Lee

Minjae Lee is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Automotive Engineering, having authored 16 papers that have together received 318 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Speech Recognition and Synthesis (3 papers) and Speech and Audio Processing (2 papers). The work is most often cited by research in Signal Processing (195 citations), Computer Graphics and Computer-Aided Design (25 citations) and Artificial Intelligence (224 citations). Minjae Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Joon Son Chung, Soyeon Choe, Jaesung Huh, Sunghwan Jung, Bong‐Jin Lee, Seongkyu Mun, Bo Zhu, Ronald Fedkiw, Ken Museth and Seoung Bum Kim. Their work appears in journals such as Sensors, ACM Transactions on Graphics and Information Sciences.

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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