Naoki Saito
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Computational Mechanics top 10%
- Co-authors
- Ronald R. CoifmanGregory BeylkinRobert BurridgeZhihua ZhangAlain RabauteMichael HerronT. S. RamakrishnanYuji Nakatsukasa
- Topics
- Image and Signal Denoising Methods (32 papers)Medical Image Segmentation Techniques (7 papers)Digital Filter Design and Implementation (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Transactions on Signal Processing
- Partner nations
- United StatesJapanChina
In The Last Decade
Naoki Saito
61 papers receiving 987 citations
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 520
- Signal Processing 248
- Artificial Intelligence 179
- Control and Systems Engineering 108
- Computational Mechanics 106
Countries citing papers authored by Naoki Saito
This map shows the geographic impact of Naoki Saito'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 Naoki Saito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naoki Saito more than expected).
Fields of papers citing papers by Naoki Saito
This network shows the impact of papers produced by Naoki Saito. 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 Naoki Saito. The network helps show where Naoki Saito may publish in the future.
Co-authorship network of co-authors of Naoki Saito
This figure shows the co-authorship network connecting the top 25 collaborators of Naoki Saito. A scholar is included among the top collaborators of Naoki Saito 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 Naoki Saito. Naoki Saito is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 17 | |
| 8 | 18 | |
| 9 | 0 | |
| 10 | On the Phase Transition Phenomenon of Graph Laplacian Eigenfunctions on Trees (Recent development and scientific applications in wavelet analysis) | 2 |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 10 | |
| 14 | 46 | |
| 15 | 20 | |
| 16 | 21 | |
| 17 | 2 | |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 16 |
About Naoki Saito
Naoki Saito is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics and Signal Processing, having authored 62 papers that have together received 1.1k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (32 papers), Medical Image Segmentation Techniques (7 papers) and Digital Filter Design and Implementation (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (520 citations), Signal Processing (248 citations) and Media Technology (101 citations). Naoki Saito has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Ronald R. Coifman, Gregory Beylkin, Robert Burridge, Zhihua Zhang, Alain Rabaute, Michael Herron, T. S. Ramakrishnan, Yuji Nakatsukasa, L. Schwartz and Edmund J. Fordham. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Signal Processing.
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.