Tsuyoshi Idé

49 papers receiving 1.0k citations

Peers

Tsuyoshi Idé
Comparison fields: 5 of 123
  • Transportation 104
  • Signal Processing 150
  • Computational Mathematics 8
  • Artificial Intelligence 373
  • Computer Vision and Pattern Recognition 213
Replace Hongbo Liu with:
Hongbo Liu China
Matthew Graham United Kingdom
Andrew Gordon Wilson United States
He Yan China
Ming Liu China
Allon G. Percus United States
Federico Monti Italy
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Nicolas Tremblay France
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Citations per year

Countries citing papers authored by Tsuyoshi Idé

Since Specialization
Citations

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

Fields of papers citing papers by Tsuyoshi Idé

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tsuyoshi Idé, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tsuyoshi Idé Line = papers co-authored together Tsuyoshi Idé links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009206
2 2004155
3 200963
4 200558
5 200753
6 201149
7 200944
8 200038
9 200334
10 200730
11 199825
12 201824
13
Predicting Nocturnal Hypoglycemia from Continuous Glucose Monitoring Data with Extended Prediction Horizon.
201923
14 201322
15 201220
16 201519
17 202218
18
Solving inverse problem of Markov chain with partial observations
201318
19 201618
20 200317

About Tsuyoshi Idé

Tsuyoshi Idé is a scholar working on Artificial Intelligence, Control and Systems Engineering, Information Systems, Atomic and Molecular Physics, and Optics and Computer Networks and Communications, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (10 papers), Time Series Analysis and Forecasting (5 papers), Fault Detection and Control Systems (4 papers), Computer Graphics and Visualization Techniques (4 papers), Color Science and Applications (4 papers), Physics of Superconductivity and Magnetism (4 papers), Advanced Condensed Matter Physics (3 papers) and Control Systems and Identification (3 papers). The work is most often cited by research in Transportation (104 citations), Signal Processing (150 citations), Computational Mathematics (8 citations), Artificial Intelligence (373 citations) and Computer Vision and Pattern Recognition (213 citations). Tsuyoshi Idé has collaborated with scholars based in United States, Japan and Russia. Frequent co-authors include Hisashi Kashima, Masashi Sugiyama, Jun Sese, Shinichi Nakajima, Akio Kotani, Keisuke Inoue, Spiros Papadimitriou, Michail Vlachos, Aurélie Lozano and Koji Tsuda. Their work appears in journals such as Journal of the Physical Society of Japan, Knowledge and Information Systems, Journal of the Society for Information Display, Journal of the Optical Society of America A and IEEE Transactions on Intelligent Transportation Systems.

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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