Hideki Asoh

3.2k total citations
103 papers, 1.5k citations indexed

About

Hideki Asoh is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hideki Asoh has authored 103 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 38 papers in Signal Processing and 34 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hideki Asoh's work include Speech and Audio Processing (23 papers), Blind Source Separation Techniques (11 papers) and Neural Networks and Applications (11 papers). Hideki Asoh is often cited by papers focused on Speech and Audio Processing (23 papers), Blind Source Separation Techniques (11 papers) and Neural Networks and Applications (11 papers). Hideki Asoh collaborates with scholars based in Japan, United States and Poland. Hideki Asoh's co-authors include Toshihiro Matsui, Futoshi Asano, Isao Hara, F. Asano, Shotaro Akaho, Suguru Kanoga, Satoru Hayamizu, Toshihiro Kamishima, Atsunori Kanemura and Yoichi Motomura and has published in prestigious journals such as PLoS ONE, NeuroImage and IEEE Access.

In The Last Decade

Hideki Asoh

98 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hideki Asoh Japan 21 548 543 377 213 194 103 1.5k
Kazunori Komatani Japan 22 787 1.4× 1.1k 2.0× 624 1.7× 208 1.0× 147 0.8× 189 2.0k
Gernot A. Fink Germany 29 1.1k 2.0× 613 1.1× 1.8k 4.8× 198 0.9× 118 0.6× 174 2.9k
Bo Sun China 24 344 0.6× 162 0.3× 904 2.4× 114 0.5× 214 1.1× 161 1.8k
Jhing-Fa Wang Taiwan 23 717 1.3× 921 1.7× 1.0k 2.7× 80 0.4× 93 0.5× 233 2.3k
Jianwu Dang China 27 1.7k 3.1× 1.3k 2.5× 323 0.9× 63 0.3× 95 0.5× 347 3.0k
William W. Armstrong Canada 11 476 0.9× 238 0.4× 121 0.3× 167 0.8× 55 0.3× 34 1.2k
Satoru Hayamizu Japan 19 515 0.9× 472 0.9× 323 0.9× 126 0.6× 105 0.5× 108 1.2k
Gerasimos Potamianos United States 26 682 1.2× 1.6k 2.9× 981 2.6× 86 0.4× 144 0.7× 139 2.3k
Siome Goldenstein Brazil 24 299 0.5× 266 0.5× 1.2k 3.1× 76 0.4× 107 0.6× 77 2.0k
Juhan Nam South Korea 16 875 1.6× 952 1.8× 1.2k 3.1× 76 0.4× 82 0.4× 83 2.2k

Countries citing papers authored by Hideki Asoh

Since Specialization
Citations

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

Fields of papers citing papers by Hideki Asoh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hideki Asoh

This figure shows the co-authorship network connecting the top 25 collaborators of Hideki Asoh. A scholar is included among the top collaborators of Hideki Asoh 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 Hideki Asoh. Hideki Asoh 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.
Nakada, Hidemoto & Hideki Asoh. (2023). End-To-End Training Of Object Segmentation Task And Video Question-Answering Task. 1–5. 1 indexed citations
2.
Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, & Jun Sakuma. (2014). Correcting Popularity Bias by Enhancing Recommendation Neutrality.. Conference on Recommender Systems. 31 indexed citations
3.
Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, & Jun Sakuma. (2013). Efficiency Improvement of Neutrality-Enhanced Recommendation.. Conference on Recommender Systems. 1–8. 17 indexed citations
4.
Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, & Jun Sakuma. (2012). Enhancement of the Neutrality in Recommendation.. Conference on Recommender Systems. 8–14. 23 indexed citations
5.
Matsusaka, Yosuke, Hideki Asoh, Isao Hara, & Futoshi Asano. (2012). Specification and Implementation of Open Source Software Suite for Realizing Communication Intelligence. Journal of Robotics and Mechatronics. 24(1). 86–94. 3 indexed citations
6.
Inoue, Yutaka, Takeshi Ikeda, Kiyoshi Yamamoto, et al.. (2008). Indoor Autonomous Positioning System on Smartphones using ComPass Beacon Device. 2008(18). 195–202. 2 indexed citations
7.
Kondō, Makoto, et al.. (2008). Construction and Evaluation of a Dialog System Based on Mapping Sentence Meanings to the Dialog Context. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics. 20(5). 732–756.
8.
Kawamoto, Mitsuru, et al.. (2007). Tracking a varying number of sound sources using particle filtering. 123–128. 2 indexed citations
9.
Matsusaka, Yosuke, Hideki Asoh, & Futoshi Asano. (2007). Multi Human Trajectory Estimation Using Stochastic Sampling and Its Application to Meeting Recognition.. Machine Vision and Applications. 5–8. 1 indexed citations
10.
Takagi, Akira, et al.. (2006). Semantic Representation for Understanding Meaning Based on Correspondence Between Meanings. Journal of Advanced Computational Intelligence and Intelligent Informatics. 10(6). 876–912. 1 indexed citations
11.
Asano, Futoshi & Hideki Asoh. (2004). Sound Source Localization and Separation Based on the EM Algorithm. Conference of the International Speech Communication Association. 37. 3 indexed citations
12.
Asano, Futoshi & Hideki Asoh. (2004). A Basic Study on the Sound Localization and Separation of Multiple Moving Sources using EM algorithm. IEICE technical report. Speech. 104(30). 1–6. 1 indexed citations
13.
Asoh, Hideki, Futoshi Asano, Yoichi Motomura, et al.. (2004). An application of a particle filter to Bayesian multiple sound source tracking with audio and video information fusion. International Conference on Information Fusion. 2. 805–812. 25 indexed citations
14.
Hamanaka, Masatoshi, Masataka Goto, Hideki Asoh, & Nobuyuki Otsu. (2003). A Learning-Based Quantization: Unsupervised Estimation of the Model Parameters. The Journal of the Abraham Lincoln Association. 2003. 18 indexed citations
15.
Hamanaka, Masatoshi, Masataka Goto, Hideki Asoh, & Nobuyuki Otsu. (2003). A learning-based jam session system that imitates a player's personality model. International Joint Conference on Artificial Intelligence. 51–58. 13 indexed citations
16.
Kanerva, Pentti, et al.. (2001). Foundations of real-world intelligence. 31 indexed citations
17.
Asano, Futoshi, Hideki Asoh, & Toshihiro Matsui. (2000). Sound Source Localization and Separation in Near Field. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 83(11). 2286–2294. 30 indexed citations
18.
Asoh, Hideki, et al.. (1998). Emergence of Expert Modules for Mobile Robot Navigation from a Mixture of Elman Networks. International Conference on Neural Information Processing. 256–259. 1 indexed citations
19.
Asoh, Hideki, Satoru Hayamizu, Isao Hara, et al.. (1997). Socially embedded learning of the office-conversant mobile robot Jijo-2. International Joint Conference on Artificial Intelligence. 2. 880–885. 68 indexed citations
20.
Motomura, Yoichi, Isao Hara, Hideki Asoh, & Toshihiro Matsui. (1997). Bayesian Network that Learns Conditional Probabilities by Neural Networks.. International Conference on Neural Information Processing. 5 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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