Shoji Nishimura

1.2k total citations
72 papers, 770 citations indexed

About

Shoji Nishimura is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Artificial Intelligence. According to data from OpenAlex, Shoji Nishimura has authored 72 papers receiving a total of 770 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 12 papers in Information Systems and 10 papers in Artificial Intelligence. Recurrent topics in Shoji Nishimura's work include Human Pose and Action Recognition (14 papers), Video Surveillance and Tracking Methods (11 papers) and Data Management and Algorithms (7 papers). Shoji Nishimura is often cited by papers focused on Human Pose and Action Recognition (14 papers), Video Surveillance and Tracking Methods (11 papers) and Data Management and Algorithms (7 papers). Shoji Nishimura collaborates with scholars based in Japan, China and United States. Shoji Nishimura's co-authors include Divyakant Agrawal, Sudipto Das, Amr El Abbadi, Qun Jin, Seppo Tella, Anne Nevgi, Atsushi Ogihara, Jianquan Liu, Bo Wu and Haruo Yokota and has published in prestigious journals such as IEEE Access, Sensors and Cancers.

In The Last Decade

Shoji Nishimura

63 papers receiving 727 citations

Peers

Shoji Nishimura

CNC

CVPR

Katayoun Farrahi United Kingdom

Manuel Stein Germany

Ibrar Hussain Pakistan

Elena Verdú Spain

Xiao Zheng United States

Manos Papagelis Canada

Jean-Paul Calbimonte Switzerland

Kristóf Fodor Hungary

Michele Girolami Italy

Katayoun Farrahi United Kingdom

Shoji Nishimura

107 ×0.3

CNC

118 ×0.5

122 ×0.5

188 ×1.1

CVPR

126 ×1.5

Citations per year, relative to Shoji Nishimura Shoji Nishimura (= 1×) peers Katayoun Farrahi

Countries citing papers authored by Shoji Nishimura

Since Specialization

Citations

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

Fields of papers citing papers by Shoji Nishimura

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shoji Nishimura

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

All Works

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20 of 20 papers shown

Wu, Bo, et al.. (2025). Integrating Acupuncture and Herbal Medicine into Assisted Reproductive Technology: A Systematic Review and Meta-Analysis of East Asian Traditional Medicine. Healthcare. 13(11). 1326–1326. 1 indexed citations

Ogihara, Atsushi, et al.. (2025). Research on predicting the sleep status of orthopedic pain patients based on machine learning. 6(1). 200201–200201. 1 indexed citations

Nishimura, Shoji, et al.. (2025). Exploratory and Interpretable Approach to Estimating Latent Health Risk Factors Without Using Domain Knowledge. Big Data Mining and Analytics. 8(2). 447–457.

Nishimura, Shoji, et al.. (2024). Multiple feature selection based on an optimization strategy for causal analysis of health data. Health Information Science and Systems. 12(1). 52–52. 2 indexed citations

Wu, Bo, et al.. (2023). Behavioral Analysis of Mowing Workers Based on Hilbert–Huang Transform: An Auxiliary Movement Analysis of Manual Mowing on the Slopes of Terraced Rice Fields. Agriculture. 13(2). 489–489. 2 indexed citations

Fujita, Naoki, Masaki Momota, Itsuto Hamano, et al.. (2023). Combination of Muscle Quantity and Quality Is Useful to Assess the Necessity of Surveillance after a 5-Year Cancer-Free Period in Patients Who Undergo Radical Cystectomy: A Multi-Institutional Retrospective Study. Cancers. 15(5). 1489–1489. 2 indexed citations

Wu, Bo, et al.. (2022). Analysis on the Subdivision of Skilled Mowing Movements on Slopes. Sensors. 22(4). 1372–1372. 6 indexed citations

Jin, Qun, et al.. (2022). Effectiveness, Policy, and User Acceptance of COVID-19 Contact-Tracing Apps in the Post–COVID-19 Pandemic Era: Experience and Comparative Study. JMIR Public Health and Surveillance. 8(10). e40233–e40233. 9 indexed citations

Wu, Bo, et al.. (2020). Analyzing the Effects of Driving Experience on Prebraking Behaviors Based on Data Collected by Motion Capture Devices. IEEE Access. 8. 197337–197351. 17 indexed citations

10.

Wu, Bo, et al.. (2020). Mowing Patterns Comparison: Analyzing the Mowing Behaviors of Elderly Adults on an Inclined Plane via a Motion Capture Device. IEEE Access. 8. 216623–216633. 11 indexed citations

11.

Nishimura, Shoji, et al.. (2019). A Fast and Robust Re-Identification Method for Large Video Data. 252–257. 1 indexed citations

12.

Wu, Bo, et al.. (2019). Culture-Based Color Influence Paths Analysis by Using Eye-Tracking Devices. 66–71. 6 indexed citations

13.

Ogihara, Atsushi, et al.. (2018). Analyzing the changes of health condition and social capital of elderly people using wearable devices. Health Information Science and Systems. 6(1). 4–4. 25 indexed citations

14.

Zhou, Xiaokang, et al.. (2017). Cyber-Enabled Well-Being Oriented Daily Living Support Based on Personal Data Analysis. IEEE Transactions on Emerging Topics in Computing. 8(2). 493–502. 24 indexed citations

15.

Nishimura, Shoji, et al.. (2016). Personal data analytics for well-being oriented life support: Experiment and feasibility study. 282. 172–179. 1 indexed citations

16.

Zhou, Xiaokang, et al.. (2013). Capturing unselfconscious information seeking behavior by analyzing gaze patterns via eye tracking experiments. 1–6.

17.

Das, Sudipto, Shoji Nishimura, Divyakant Agrawal, & Amr El Abbadi. (2011). Albatross. Proceedings of the VLDB Endowment. 4(8). 494–505. 121 indexed citations

18.

Nevgi, Anne, Seppo Tella, & Shoji Nishimura. (2010). University teachers' approaches to teaching and their pedagogical use of ICT : A comparative case study of Finland, Japan and India. Työväentutkimus Vuosikirja. 7(7). 1–14. 1 indexed citations

19.

Nishimura, Shoji, et al.. (2006). Using iPods to Support Content Area Learning in a Japanese College Lecture Course. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2006(1). 3014–3019. 5 indexed citations

20.

Maeno, Yoshiharu, et al.. (2004). Polimatica: abstraction for customizable private virtual organizations in global grids. 674–681. 2 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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