S. Ninomiya

3.6k total citations
176 papers, 2.7k citations indexed

About

S. Ninomiya is a scholar working on Plant Science, Ecology and Analytical Chemistry. According to data from OpenAlex, S. Ninomiya has authored 176 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Plant Science, 20 papers in Ecology and 19 papers in Analytical Chemistry. Recurrent topics in S. Ninomiya's work include Smart Agriculture and AI (48 papers), Leaf Properties and Growth Measurement (25 papers) and Remote Sensing in Agriculture (20 papers). S. Ninomiya is often cited by papers focused on Smart Agriculture and AI (48 papers), Leaf Properties and Growth Measurement (25 papers) and Remote Sensing in Agriculture (20 papers). S. Ninomiya collaborates with scholars based in Japan, China and Egypt. S. Ninomiya's co-authors include Wei Guo, Hiroyoshi Iwata, Yosuke Yoshioka, Kyosuke Yamamoto, R. Uday Kiran, Ryo Ohsawa, Bangyou Zheng, Masayuki Hirafuji, Tokihiro Fukatsu and Yue Mu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

S. Ninomiya

156 papers receiving 2.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
S. Ninomiya Japan 28 1.8k 771 479 415 193 176 2.7k
Hemerson Pistori Brazil 24 1.4k 0.8× 773 1.0× 410 0.9× 381 0.9× 135 0.7× 104 2.6k
S. A. Shearer United States 27 1.3k 0.7× 771 1.0× 314 0.7× 693 1.7× 69 0.4× 139 3.3k
Wenshan Guo China 33 2.3k 1.3× 1.1k 1.4× 362 0.8× 606 1.5× 76 0.4× 129 3.4k
Frank Liebisch Switzerland 27 1.6k 0.9× 1.2k 1.6× 246 0.5× 573 1.4× 136 0.7× 62 2.7k
Simon Pearson United Kingdom 30 2.6k 1.4× 599 0.8× 358 0.7× 308 0.7× 95 0.5× 128 4.5k
Shawn C. Kefauver Spain 27 1.9k 1.1× 1.5k 2.0× 338 0.7× 575 1.4× 313 1.6× 91 3.0k
Arti Singh United States 26 2.8k 1.6× 995 1.3× 690 1.4× 228 0.5× 440 2.3× 72 3.5k
Chenghai Yang United States 37 1.7k 1.0× 2.4k 3.1× 551 1.2× 1.1k 2.6× 77 0.4× 169 4.1k
Yue Shi China 26 1.2k 0.6× 1.4k 1.8× 420 0.9× 424 1.0× 50 0.3× 70 3.0k

Countries citing papers authored by S. Ninomiya

Since Specialization
Citations

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

Fields of papers citing papers by S. Ninomiya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Ninomiya

This figure shows the co-authorship network connecting the top 25 collaborators of S. Ninomiya. A scholar is included among the top collaborators of S. Ninomiya 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 S. Ninomiya. S. Ninomiya 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.
Wang, Huimin, Hao Yin, Haitao Li, et al.. (2024). Quantitative 2D fruit shape analysis of a wide range of pear genetic resources toward shape design breeding. Scientia Horticulturae. 327. 112826–112826. 4 indexed citations
2.
3.
Li, Haitao, Shutian Tao, Hao Yin, et al.. (2023). Automatic Branch–Leaf Segmentation and Leaf Phenotypic Parameter Estimation of Pear Trees Based on Three-Dimensional Point Clouds. Sensors. 23(9). 4572–4572. 13 indexed citations
4.
Ismail, Roslan, et al.. (2023). The effect of calcium silicate and ground magnesium limestone (GML) on the chemical characteristics of acid sulfate soil. PLoS ONE. 18(9). e0290703–e0290703. 3 indexed citations
5.
Wang, Haozhou, Yulin Duan, Yun Shi, et al.. (2021). EasyIDP: A Python Package for Intermediate Data Processing in UAV-Based Plant Phenotyping. Remote Sensing. 13(13). 2622–2622. 23 indexed citations
6.
Wang, Haozhou, et al.. (2021). EasyDCP: An affordable, high‐throughput tool to measure plant phenotypic traits in 3D. Methods in Ecology and Evolution. 12(9). 1679–1686. 14 indexed citations
7.
Guo, Wei, et al.. (2019). An Adaptive Supervision Framework for Active Learning in Object Detection.. Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad). 230. 4 indexed citations
8.
Ninomiya, S., et al.. (2013). Development of an Open Field Server and Sensor Cloud System. Agricultural Information Research. 22(1). 60–70. 3 indexed citations
9.
Tanaka, Kei, et al.. (2011). Tool for Predicting the Possibility of Rice Cultivation Using SIMRIW. Agricultural Information Research. 20(1). 1–12. 5 indexed citations
10.
Hirafuji, Masayuki, et al.. (2010). Deployment and improvement of Field Servers in India. Society of Instrument and Control Engineers of Japan. 2925–2927.
11.
Yoshikawa, Seiko, et al.. (2010). Estimation of pollution load from the Okayama and Kagawa basins flowing into the Seto Inland Sea in light of their basin characteristics. Japanese Journal of Limnology (Rikusuigaku Zasshi). 71(3). 269–284. 2 indexed citations
12.
Ninomiya, S., et al.. (2008). eLearning for international agriculture development: Dealing with challenges. The International Journal of Education and Development using Information and Communication Technology (The University of the West Indies). 4(1). 80–94. 8 indexed citations
13.
Sánchez‐Alonso, Salvador, et al.. (2008). Engineering an ontology on organic agriculture and agroecology: the case of the Organic.Edunet project.. 53(5). 503–510. 3 indexed citations
14.
Ninomiya, S., et al.. (2007). eLearning in Higher Education Makes Its Debut in Cambodia: Implications of the Provincial Business Education Project. SHILAP Revista de lepidopterología. 1 indexed citations
15.
Ninomiya, S., et al.. (2007). e-Learning in Higher Education Makes Its Debut in Cambodia: The Provincial Business Education Project.. The International Review of Research in Open and Distributed Learning. 8(1). 1–14. 13 indexed citations
16.
Adinarayana, J., et al.. (2006). Web-based Decision Support System for Rural Land Use Planning-WebLUP-a Prototype. eCommons (Cornell University). 8 indexed citations
17.
Ninomiya, S., et al.. (2006). Development of a Gateway-P2P-Node for Enhancing the Function of BIX Image Broker System. Agricultural Information Research. 15(3). 281–292. 2 indexed citations
18.
Ninomiya, S., et al.. (2006). Development of Image Broker System Using P2P for Sharing of Agricultural Products Image. Agricultural Information Research. 15(2). 155–164. 5 indexed citations
19.
Ninomiya, S.. (2001). The present status and perspective of research projects for agricultural information technologies in MAFF. Journal of the Japanese Society of Agricultural Machinery. 63(4). 4–11. 3 indexed citations
20.
Roy, Kingshuk, et al.. (2000). Visible agriculture by FARMWEB, an advanced web-based farming database system - in case of acquiring three dimensional (3D) images of melon fruits.. Agricultural Information Research. 9(1). 1–14. 4 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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