Munchurl Kim
researcher
Facts
12 properties- Instance of
- human
- Date of birth
- 1967
- Country of citizenship
- South Korea[3]
- Occupation
- researcher
- Employer
- KAIST (2013–present), KAIST (2009–2013), Electronics and Telecommunications Research Institute (1997–2001)[4][5][6]
- Doctoral advisor
- José Príncipe[9]
- Doctoral student
- Juan Luis Gonzalez Bello[11]
- Given name
- Mun-cheol[13]
- Imported from
- wholeness_audit_2026-05-02
🏷️ Also known as
en Munchurl Kim
ko 김문철
zh 金紋哲
🔖 Identifiers · 13
- ISNI
- 0000000464354422
- ORCID iD
- 0000-0003-0146-5419
- VIAF cluster ID
- 55152138529210981180
- OpenAlex ID
- A5027012300, A5070940109, A5115409573, A5130749335, A5139926582, A5149905860as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
- Academic Tree ID
- 814109
- DBLP author ID
- 84/4965
- Dimensions author ID
- 012003040221.38
- Google Scholar author ID
- bGXte_4AAAAJ
- IEEE Xplore author ID
- 37291553900
- National Library of Korea ID
- KAC201804375
- OpenReview.net profile ID
- Munchurl_Kim1
- ResearchGate profile ID
- Munchurl-Kim
Show all 13 identifiers +1
- Semantic Scholar author ID
- 144366095
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 44
2X Super-Resolution Hardware Using Edge-Orientation-Based Linear Mapping for Real-Time 4K UHD 60 fps Video Applications,
A DCT-Based Total JND Profile for Spatiotemporal and Foveated Masking Effects,
A Deep Convolutional Neural Network with Selection Units for Super-Resolution,
A Deep Motion Deblurring Network Based on Per-Pixel Adaptive Kernels With Residual Down-Up and Up-Down Modules,
A Frame-Level Constant Bit-Rate Control Using Recursive Bayesian Estimation for Versatile Video Coding,
A Hybrid Architecture of Jointly Learning Image Compression and Quality Enhancement with Improved Entropy Minimization.,
AIM 2019 Challenge on Bokeh Effect Synthesis: Methods and Results,
An All-Zero Block Detection Scheme for Low-Complexity HEVC Encoders
+36 more
← Authored by 44
2X Super-Resolution Hardware Using Edge-Orientation-Based Linear Mapping for Real-Time 4K UHD 60 fps Video Applications,
A DCT-Based Total JND Profile for Spatiotemporal and Foveated Masking Effects,
A Deep Convolutional Neural Network with Selection Units for Super-Resolution,
A Deep Motion Deblurring Network Based on Per-Pixel Adaptive Kernels With Residual Down-Up and Up-Down Modules,
A Frame-Level Constant Bit-Rate Control Using Recursive Bayesian Estimation for Versatile Video Coding,
A Hybrid Architecture of Jointly Learning Image Compression and Quality Enhancement with Improved Entropy Minimization.,
AIM 2019 Challenge on Bokeh Effect Synthesis: Methods and Results,
An All-Zero Block Detection Scheme for Low-Complexity HEVC Encoders
+36 more
Affiliated with 3
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Summary
Munchurl Kim was born in 1967[1]. He worked as a researcher[2].
Body
Education
Educated at Kyungpook National University[7], a university[14], in South Korea[15], founded in 1946[16] and University of Florida[8], a public research university[17], in United States[18], founded in 1853[19], headquartered in Gainesville[20].
Career and Affiliations
Employers include KAIST[4], a public research university[21], in South Korea[22], founded in 1971[23], headquartered in Daejeon[24] and Electronics and Telecommunications Research Institute[6], a research institute[25], in South Korea[26], founded in 1976[27].
FAQs
What did Munchurl Kim do for work?
Munchurl Kim worked as researcher[2].
Where did Munchurl Kim go to school?
Munchurl Kim was educated at Kyungpook National University[7] and University of Florida[8].