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Koki Karube

ResearcherPublications, citations & collaboration network

Koki Karube is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 13 works, 1 citations, an h-index of 1 and an i10-index of 0.

13
Works
1
Citations
1
h-index
0
i10-index

How has Koki Karube's publication output changed over time?

ScholarIQpublication output · 2022–2025

Output grew400% over the shown period — from 1 works in 2022 to 5 in 2025.

1
2
2
5
2022202320242025

What are the most-cited papers on Koki Karube?

ScholarIQmost cited works
Disassembly Work Analysis Using Motion Capture and Machine Learning
Taku Hayashi, Koki Karube, Masao Sugi, Tetsuo Yamada
Lecture notes in mechanical engineering. 20241 Citations
Rehabilitation Layout Planning for Elderly Daytime Care Service for Total Flow of Staffs and Remoteness of Equipment
Koki Karube, Hiromasa Ijuin, Masato Takanokura, Munenori Kakehi, Tetsuo Yamada
EPiC series in computing. 20220 CitationsOPEN ACCESS
Multi-goal Rehabilitation Layout Planning for Total Flow of Staffs and Remoteness of Equipment in Elderly Daytime Care Service
Tetsuo Yamada, Koki Karube, Hiromasa Ijuin, Masato Takanokura, Munenori Kakehi
Information Engineering Express. 20230 CitationsOPEN ACCESS
Identification of potential improvement assembly movements using worker classification by motion capture and machine learning
Ryuto Kawane, Hiromasa Ijuin, Koki Karube, Masao Sugi, Tomohiro Nakada, Tetsuo Yamada
20230 Citations
Motion Capture Analysis of Learning Effect for Assembly Tasks
Koki Karube, Ryuto Kawane, Taku Hayashi, Masao Sugi, Tetsuo Yamada
Lecture notes in mechanical engineering. 20240 Citations

Related on ScholarIQ

University of Electro-Communications
Institution
Disassembly Work Analysis Using Motion Capture and Machine Learning
Paper
Rehabilitation Layout Planning for Elderly Daytime Care Service for Total Flow of Staffs and Remoteness of Equipment
Paper
Multi-goal Rehabilitation Layout Planning for Total Flow of Staffs and Remoteness of Equipment in Elderly Daytime Care Service
Paper
Identification of potential improvement assembly movements using worker classification by motion capture and machine learning
Paper
Motion Capture Analysis of Learning Effect for Assembly Tasks
Paper
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