Yusuke Iwasawa

2.3k total citations
45 papers, 401 citations indexed

About

Yusuke Iwasawa is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Science Applications. According to data from OpenAlex, Yusuke Iwasawa has authored 45 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 6 papers in Computer Science Applications. Recurrent topics in Yusuke Iwasawa's work include Topic Modeling (8 papers), Context-Aware Activity Recognition Systems (6 papers) and Natural Language Processing Techniques (6 papers). Yusuke Iwasawa is often cited by papers focused on Topic Modeling (8 papers), Context-Aware Activity Recognition Systems (6 papers) and Natural Language Processing Techniques (6 papers). Yusuke Iwasawa collaborates with scholars based in Japan, United States and South Korea. Yusuke Iwasawa's co-authors include Yutaka Matsuo, Yutaka Matsuo, Kotaro Nakayama, Bo Yang, Gen Hattori, Jianming Wu, Kazushi Ikeda, Takeshi Kojima, Shixiang Gu and Masahiro Suzuki and has published in prestigious journals such as Remote Sensing, Machine Learning and Pattern Recognition Letters.

In The Last Decade

Yusuke Iwasawa

32 papers receiving 393 citations

Peers

Yusuke Iwasawa
Comparison fields: 5 of 76
  • Artificial Intelligence 267
  • Computer Vision and Pattern Recognition 147
  • Computer Science Applications 114
  • Control and Systems Engineering 30
  • Information Systems 29
Replace Claudio Martella with:
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Chunyan Zeng China
Wolfgang Wahlster Germany
Morihiko Tamai Japan
Wenqiang Jin China
John Funge United States
Ajai Kumar India
Daniel Hládek Slovakia
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Citations per field, relative to Yusuke Iwasawa
Yusuke Iwasawa · 1×
Citations per year, relative to Yusuke Iwasawa
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Countries citing papers authored by Yusuke Iwasawa

Since Specialization
Citations

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

Fields of papers citing papers by Yusuke Iwasawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yusuke Iwasawa

This figure shows the co-authorship network connecting the top 25 collaborators of Yusuke Iwasawa. A scholar is included among the top collaborators of Yusuke Iwasawa 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 Yusuke Iwasawa. Yusuke Iwasawa 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
# Work Indexed citations
1 0
2 0
3 0
4 0
5 0
6 4
7 3
8 0
9 9
10 2
11 23
12 11
13
Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization
63
14 1
15 5
16 150
17
Neuron as an Agent
2
18
Extending Robust Adversarial Reinforcement Learning Considering Adaptation and Diversity.
5
19
Toward learning better metrics for sequence generation training with policy gradient
1
20 0

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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