Daigo Muramatsu

2.8k total citations · 2 hit papers
79 papers, 1.8k citations indexed

About

Daigo Muramatsu is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Signal Processing. According to data from OpenAlex, Daigo Muramatsu has authored 79 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Computer Vision and Pattern Recognition, 52 papers in Biomedical Engineering and 14 papers in Signal Processing. Recurrent topics in Daigo Muramatsu's work include Gait Recognition and Analysis (47 papers), Human Pose and Action Recognition (35 papers) and Video Surveillance and Tracking Methods (24 papers). Daigo Muramatsu is often cited by papers focused on Gait Recognition and Analysis (47 papers), Human Pose and Action Recognition (35 papers) and Video Surveillance and Tracking Methods (24 papers). Daigo Muramatsu collaborates with scholars based in Japan, China and Iran. Daigo Muramatsu's co-authors include Yasushi Yagi, Yasushi Makihara, Tomio Echigo, Noriko Takemura, Takashi Matsumoto, Md. Zasim Uddin, Haruyuki Iwama, Xiang Li, Trung Thanh Ngo and Atsuyuki Suzuki and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Daigo Muramatsu

75 papers receiving 1.8k citations

Hit Papers

GEINet: View-invariant gait recognition using a convoluti... 2016 2026 2019 2022 2016 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daigo Muramatsu Japan 20 1.5k 1.5k 457 266 252 79 1.8k
Davrondzhon Gafurov Norway 14 623 0.4× 458 0.3× 183 0.4× 218 0.8× 57 0.2× 29 984
Naresh P. Cuntoor United States 11 570 0.4× 657 0.4× 197 0.4× 209 0.8× 20 0.1× 18 802
Tieniu Tan China 12 329 0.2× 885 0.6× 139 0.3× 217 0.8× 12 0.0× 31 1.1k
Chiraz BenAbdelkader United States 11 443 0.3× 612 0.4× 167 0.4× 137 0.5× 19 0.1× 19 736
Wataru Takano Japan 17 276 0.2× 656 0.4× 194 0.4× 339 1.3× 31 0.1× 76 1.1k
Yingnan Sun United Kingdom 11 199 0.1× 133 0.1× 37 0.1× 64 0.2× 11 0.0× 18 675
Austin Myers United States 5 215 0.1× 728 0.5× 41 0.1× 446 1.7× 3 0.0× 7 1.2k
Santosh Kumar Yadav India 8 153 0.1× 437 0.3× 98 0.2× 122 0.5× 11 0.0× 36 606
Muhammad Muaaz Norway 13 212 0.1× 193 0.1× 80 0.2× 126 0.5× 13 0.1× 24 572
Joyeeta Singha India 15 136 0.1× 456 0.3× 319 0.7× 80 0.3× 5 0.0× 29 676

Countries citing papers authored by Daigo Muramatsu

Since Specialization
Citations

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

Fields of papers citing papers by Daigo Muramatsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daigo Muramatsu

This figure shows the co-authorship network connecting the top 25 collaborators of Daigo Muramatsu. A scholar is included among the top collaborators of Daigo Muramatsu 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 Daigo Muramatsu. Daigo Muramatsu 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.
Makihara, Yasushi, et al.. (2023). Batch Hard Contrastive Loss and Its Application to Cross-View Gait Recognition. IEEE Access. 11. 31177–31187. 1 indexed citations
2.
Okura, Fumio, et al.. (2023). Accuracy Evaluation and Prediction of Single-Image Camera Calibration. IEEE Access. 11. 19312–19323. 2 indexed citations
3.
Hasegawa, R., Akira Uchiyama, Fumio Okura, et al.. (2022). Close-Contact Detection Using a Single Camera for Sports Considering Occlusion. IEEE Access. 10. 15457–15468.
4.
Muramatsu, Daigo, et al.. (2022). Incorporation of Extra Pseudo Labels for CNN-based Gait Recognition. 1–5. 2 indexed citations
5.
Hasegawa, R., Akira Uchiyama, Daigo Muramatsu, et al.. (2021). Developing a Close-Contact Detection System Using a Single Camera for Sports Considering Occlusion. IEICE Technical Report; IEICE Tech. Rep.. 121(41). 21–26.
6.
Xu, Chi, Yasushi Makihara, Noriko Takemura, et al.. (2021). Uncertainty-Aware Gait-Based Age Estimation and its Applications. IEEE Transactions on Biometrics Behavior and Identity Science. 3(4). 479–494. 9 indexed citations
7.
Makihara, Yasushi, Daigo Muramatsu, Jianfu Zhang, et al.. (2021). Learn to Walk Across Ages: Motion Augmented Multi-Age Group Gait Video Translation. IEEE Access. 9. 40550–40559. 4 indexed citations
8.
Takemura, Noriko, Yasushi Makihara, Daigo Muramatsu, Tomio Echigo, & Yasushi Yagi. (2018). Multi-view large population gait dataset and its performance evaluation for cross-view gait recognition. SHILAP Revista de lepidopterología. 10(1). 298 indexed citations breakdown →
9.
Makihara, Yasushi, Daigo Muramatsu, Yasushi Yagi, et al.. (2015). Individuality-preserving Silhouette Extraction for Gait Recognition. 7(0). 74–78. 14 indexed citations
10.
Muramatsu, Daigo, Yasushi Makihara, & Yasushi Yagi. (2013). Quality-dependent view transformation model for cross-view gait recognition. 1–8. 6 indexed citations
11.
Muramatsu, Daigo, Haruyuki Iwama, Yasushi Makihara, & Yasushi Yagi. (2013). Multi-view multi-modal person authentication from a single walking image sequence. 1–8. 11 indexed citations
12.
Muramatsu, Daigo & Yasushi Yagi. (2013). Silhouette-based online signature verification using pen tip trajectory and pen holding style. 1–8. 1 indexed citations
13.
Muramatsu, Daigo, et al.. (2012). Arbitrary view transformation model for gait person authentication. 85–90. 33 indexed citations
14.
Muramatsu, Daigo, et al.. (2010). Camera-based online signature verification system: effects of camera positions. World Automation Congress. 1–6. 3 indexed citations
15.
Muramatsu, Daigo, et al.. (2006). A Sequential Monte Carlo Algorithm for Adaptation to Intersession Variability in On-line Signature Verification. HAL (Le Centre pour la Communication Scientifique Directe). 4 indexed citations
16.
Muramatsu, Daigo, et al.. (2003). Bayesian MCMC for biometric person authentication incorporating on-line signature trajectories. International Conference on Signal Processing. 269–273.
17.
Muramatsu, Daigo & Takashi Matsumoto. (2003). An HMM On-Line Signature Verification with Pen Position Trajectories.. International Conference on Artificial Intelligence. 299–303. 1 indexed citations
18.
Hadidi, Khayrollah, et al.. (2002). A novel highly linear CMOS buffer. 3. 369–371. 23 indexed citations
19.
Hadidi, Khayrollah, et al.. (1999). A 500MS/sec–54dB THD S/H circuit in a 0.5µm CMOS process. European Solid-State Circuits Conference. 158–161. 3 indexed citations
20.
Hadidi, Khayrollah, et al.. (1997). A 103MHz open-loop full CMOS highly-linear sample-and-hold amplifier. European Solid-State Circuits Conference. 396–399. 1 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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