Sang Min Oh

445 citations
13 papers · 292 indexed · h-index 9
Topics
Robotics and Sensor-Based Localization (5 papers)Music and Audio Processing (2 papers)Human Motion and Animation (2 papers)
Journals
Applied SciencesJournal of Korean Society for Atmospheric EnvironmentarXiv (Cornell University)

In The Last Decade

Sang Min Oh

11 papers receiving 275 citations

Peers

Sang Min Oh
Comparison fields: 5 of 63
  • Computer Vision and Pattern Recognition 160
  • Aerospace Engineering 133
  • Artificial Intelligence 70
  • Control and Systems Engineering 38
  • Environmental Engineering 29
Replace Vladimír Kubelka with:
Vladimír Kubelka Czechia
Favio R. Masson Argentina
Roberto J. López-Sastre Spain
Luchi Hua China
Ricardo Vázquez-Martín Spain
Michal Reinštein Czechia
Changhao Chen China
Randy Warner United States
Jens-Steffen Gutmann United States
Sang Min Oh relative to Vladimír Kubelka Czechia Vladimír Kubelka's profile →
Citations per field
00.5×1.7×
Vladimír Kubelka · 1×
Citations per year

Countries citing papers authored by Sang Min Oh

Since Specialization
Citations

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

Fields of papers citing papers by Sang Min Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sang Min Oh. 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 Sang Min Oh. The network helps show where Sang Min Oh may publish in the future.

Co-authorship network of co-authors of Sang Min Oh

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 7
2 8
3 0
4 5
5 0
6 8
7 12
8 54
9 107
10 17
11 25
12
A Variational inference method for Switching Linear Dynamic Systems
8
13 41

About Sang Min Oh

Sang Min Oh is a scholar working on Geology, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 292 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (5 papers), Music and Audio Processing (2 papers) and Human Motion and Animation (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Aerospace Engineering (133 citations) and Geology (14 citations). Sang Min Oh has collaborated with scholars based in United States, South Korea and Spain. Frequent co-authors include James M. Rehg, Aaron Bobick, Jie Sun, Dongshin Kim, Frank Dellaert, Tucker Balch, Bala Rajaratnam, Pablo F. Alcantarilla, Kshitij Khare and Luis M. Bergasa. Their work appears in journals such as Applied Sciences, Journal of Korean Society for Atmospheric Environment and arXiv (Cornell University).

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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