Minsu Kim

712 total citations
32 papers, 421 citations indexed

About

Minsu Kim is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Minsu Kim has authored 32 papers receiving a total of 421 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Signal Processing, 12 papers in Computer Vision and Pattern Recognition and 12 papers in Artificial Intelligence. Recurrent topics in Minsu Kim's work include Speech and Audio Processing (17 papers), Music and Audio Processing (10 papers) and Speech Recognition and Synthesis (7 papers). Minsu Kim is often cited by papers focused on Speech and Audio Processing (17 papers), Music and Audio Processing (10 papers) and Speech Recognition and Synthesis (7 papers). Minsu Kim collaborates with scholars based in South Korea, United States and Canada. Minsu Kim's co-authors include Yong Man Ro, Hoi‐Jun Yoo, Joonsoo Kwon, Seung‐Jin Lee, Jinwook Oh, Seungjin Lee, Joo-Young Kim, Kwanho Kim, Kwanho Kim and Insik Shin and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, Pattern Recognition and IEEE Internet of Things Journal.

In The Last Decade

Minsu Kim

30 papers receiving 407 citations

Peers

Minsu Kim
D.W. Redmill United Kingdom
Hima Bindu Valiveti India
Cheong-Fat Chan Hong Kong
Takehiro Moriya Japan
Mohit Kumar United States
S. Casale Italy
Guillermo Payá–Vayá Germany
S.V. Andersen Denmark
Stéphane Pateux France
Georges Quénot France
D.W. Redmill United Kingdom
Minsu Kim
Citations per year, relative to Minsu Kim Minsu Kim (= 1×) peers D.W. Redmill

Countries citing papers authored by Minsu Kim

Since Specialization
Citations

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

Fields of papers citing papers by Minsu Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minsu Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Minsu Kim. A scholar is included among the top collaborators of Minsu 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 Minsu Kim. Minsu 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
1.
Kim, Minsu, et al.. (2024). Textless Unit-to-Unit Training for Many-to-Many Multilingual Speech-to-Speech Translation. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 3934–3946. 2 indexed citations
2.
Kim, Minsu, et al.. (2024). AKVSR: Audio Knowledge Empowered Visual Speech Recognition by Compressing Audio Knowledge of a Pretrained Model. IEEE Transactions on Multimedia. 26. 6462–6474. 7 indexed citations
3.
Kim, Minsu, et al.. (2024). LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale. 15–29. 3 indexed citations
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Kim, Minsu, et al.. (2023). Deep Visual Forced Alignment: Learning to Align Transcription with Talking Face Video. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8273–8281.
9.
Kim, Minsu, et al.. (2023). Intelligible Lip-to-Speech Synthesis with Speech Units. 4349–4353. 11 indexed citations
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Kim, Minsu, et al.. (2023). Multi-Temporal Lip-Audio Memory for Visual Speech Recognition. 1–5. 7 indexed citations
12.
Kim, Minsu, et al.. (2022). Distinguishing Homophenes Using Multi-Head Visual-Audio Memory for Lip Reading. Proceedings of the AAAI Conference on Artificial Intelligence. 36(1). 1174–1182. 50 indexed citations
13.
Kim, Minsu, et al.. (2022). Visual Context-driven Audio Feature Enhancement for Robust End-to-End Audio-Visual Speech Recognition. Interspeech 2022. 2838–2842. 18 indexed citations
14.
Kim, Minsu, et al.. (2022). SyncTalkFace: Talking Face Generation with Precise Lip-Syncing via Audio-Lip Memory. Proceedings of the AAAI Conference on Artificial Intelligence. 36(2). 2062–2070. 44 indexed citations
15.
Kim, Minsu, et al.. (2021). CroMM-VSR: Cross-Modal Memory Augmented Visual Speech Recognition. IEEE Transactions on Multimedia. 24. 4342–4355. 25 indexed citations
16.
Kim, Minsu, et al.. (2021). Speech Reconstruction With Reminiscent Sound Via Visual Voice Memory. IEEE/ACM Transactions on Audio Speech and Language Processing. 29. 3654–3667. 16 indexed citations
17.
Lee, Kilho, Minsu Kim, Hayeon Kim, et al.. (2019). Fault-Resilient Real-Time Communication Using Software-Defined Networking. 204–215. 10 indexed citations
18.
Lee, Kilho, Minsu Kim, Hayeon Kim, et al.. (2019). JMC: Jitter-Based Mixed-Criticality Scheduling for Distributed Real-Time Systems. IEEE Internet of Things Journal. 6(4). 6310–6324. 1 indexed citations
19.
Kim, Kwanho, et al.. (2009). A Configurable Heterogeneous Multicore Architecture With Cellular Neural Network for Real-Time Object Recognition. IEEE Transactions on Circuits and Systems for Video Technology. 19(11). 1612–1622. 10 indexed citations
20.
Kim, Joo-Young, Kwanho Kim, Seungjin Lee, Minsu Kim, & Hoi‐Jun Yoo. (2008). A 66fps 3 8mW nearest neighbor matching processor with hierarchical VQ algorithm for real-time object recognition. 177–180. 9 indexed citations

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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2026