Hiroyuki Uga

636 total citations
10 papers, 220 citations indexed

About

Hiroyuki Uga is a scholar working on Plant Science, Ecology and Insect Science. According to data from OpenAlex, Hiroyuki Uga has authored 10 papers receiving a total of 220 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Plant Science, 4 papers in Ecology and 2 papers in Insect Science. Recurrent topics in Hiroyuki Uga's work include Smart Agriculture and AI (8 papers), Remote Sensing in Agriculture (4 papers) and Plant Virus Research Studies (4 papers). Hiroyuki Uga is often cited by papers focused on Smart Agriculture and AI (8 papers), Remote Sensing in Agriculture (4 papers) and Plant Virus Research Studies (4 papers). Hiroyuki Uga collaborates with scholars based in Japan. Hiroyuki Uga's co-authors include Hitoshi Iyatomi, Satoshi Kagiwada, Atsushi Fukuda, Nobusuke Iwasaki, Tadashi Ebihara, Koichi Mizutani, Hiroki Nakabayashi and Kenji Kubota and has published in prestigious journals such as Computers and Electronics in Agriculture, Japanese Journal of Applied Entomology and Zoology and International Journal of Engineering & Technology.

In The Last Decade

Hiroyuki Uga

10 papers receiving 202 citations

Peers

Hiroyuki Uga

PS

AC

ECOLO

CVPR

MT

Ramachandra Hebbar India

Veena I Puranikmath India

Malusi Sibiya South Africa

Gittaly Dhingra India

Vibhor Kumar Vishnoi India

Nagaratna B. Chittaragi India

Jihen Amara Tunisia

Alexis Carlier Belgium

Milan Šulc Czechia

José G. M. Esgario Brazil

Ramachandra Hebbar India

Hiroyuki Uga

320 ×1.5

PS

120 ×1.6

AC

45 ×1.3

ECOLO

16 ×1.2

CVPR

5 ×0.5

MT

Citations per year, relative to Hiroyuki Uga Hiroyuki Uga (= 1×) peers Ramachandra Hebbar

Countries citing papers authored by Hiroyuki Uga

Since Specialization

Citations

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

Fields of papers citing papers by Hiroyuki Uga

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hiroyuki Uga

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

All Works

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10 of 10 papers shown

1.

Fukuda, Atsushi, et al.. (2023). Towards robust plant disease diagnosis with hard-sample re-mining strategy. Computers and Electronics in Agriculture. 215. 108375–108375. 5 indexed citations

2.

Uga, Hiroyuki, et al.. (2021). PPIG: Productive and Pathogenic Image Generation for Plant Disease Diagnosis. 554–559. 3 indexed citations

3.

Uga, Hiroyuki, et al.. (2019). Super-Resolution for Practical Automated Plant Disease Diagnosis System. 1–6. 8 indexed citations

4.

Kubota, Kenji, et al.. (2019). Towards the Management of Whiteflies（Hemiptera: Aleyrodidae）in Greenhouse by Using Acoustic and Vibrational Methods. Japanese Journal of Applied Entomology and Zoology. 63(3). 97–107. 2 indexed citations

5.

Uga, Hiroyuki, et al.. (2018). A Practical Plant Diagnosis System for Field Leaf Images and Feature Visualization. International Journal of Engineering & Technology. 7(4.11). 49–49. 22 indexed citations

6.

Kagiwada, Satoshi, et al.. (2018). A deep learning approach for on-site plant leaf detection. 118–122. 40 indexed citations

7.

Kagiwada, Satoshi, et al.. (2018). Diagnosis of Multiple Cucumber Infections with Convolutional Neural Networks. 1–4. 12 indexed citations

8.

Kagiwada, Satoshi, et al.. (2018). An End-To-End Practical Plant Disease Diagnosis System for Wide-Angle Cucumber Images. International Journal of Engineering & Technology. 7(4.11). 106–111. 6 indexed citations

9.

Nakabayashi, Hiroki, et al.. (2017). Biotype identification of Bemisia tabaci by acoustical method. 8(3). 1 indexed citations

10.

Uga, Hiroyuki, et al.. (2016). Basic Investigation on a Robust and Practical Plant Diagnostic System. 989–992. 121 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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