Takeshi Asahi
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- Image and Signal Denoising Methods 5
- Medical Image Segmentation Techniques 2
- Media Technology top 10%
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- Advanced Numerical Analysis Techniques 3
- Sparse and Compressive Sensing Techniques 1
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- Anatomy and Medical Technology 2
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- Radiomics and Machine Learning in Medical Imaging 1
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- Photoreceptor and optogenetics research 1
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- Neural dynamics and brain function 1
- Co-authors
- Jaime H. OrtegaRodrigo LecarosGonzalo RojasMarcelo GálvezKenichi YoshikawaTakatoshi IchinoKonstantin AgladzeNobuyuki Magome
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
In The Last Decade
Takeshi Asahi
17 papers receiving 370 citations
Peers
Comparison fields: 5 of 109
- Computer Vision and Pattern Recognition 181
- Media Technology 37
- Computer Graphics and Computer-Aided Design 13
- Health Informatics 5
- Signal Processing 29
Countries citing papers authored by Takeshi Asahi
This map shows the geographic impact of Takeshi Asahi'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 Takeshi Asahi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Asahi more than expected).
Fields of papers citing papers by Takeshi Asahi
This network shows the impact of papers produced by Takeshi Asahi. 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 Takeshi Asahi. The network helps show where Takeshi Asahi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takeshi Asahi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 8 | |
| 2 | 2018 | 38 | |
| 3 | 2016 | 1 | |
| 4 | 2016 | 30 | |
| 5 | 2014 | 1 | |
| 6 | Proceedings - International Conference on Image Processing, ICIP | 2011 | 245 |
| 7 | 2009 | 6 | |
| 8 | 2008 | 22 | |
| 9 | 2008 | 2 | |
| 10 | 2007 | 11 | |
| 11 | 2004 | 1 | |
| 12 | 2004 | 1 | |
| 13 | A Computationally Efficient Algorithm for Exponential B-Splines Based on Difference/IIR Filter Approach | 2002 | 2 |
| 14 | A New Formulation for Discrete Box Splines Reducing Computational Cost and Its Evaluation | 2001 | 3 |
| 15 | An efficient algorithm for decomposition and reconstruction of images by box splines | 2001 | 3 |
| 16 | 1995 | 5 | |
| 17 | 1990 | 2 |
About Takeshi Asahi
Takeshi Asahi is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Urology, having authored 17 papers that have together received 381 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (5 papers), Advanced Numerical Analysis Techniques (3 papers), Medical Image Segmentation Techniques (2 papers), Anatomy and Medical Technology (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Sparse and Compressive Sensing Techniques (1 paper), Photoreceptor and optogenetics research (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (181 citations), Media Technology (37 citations) and Computer Graphics and Computer-Aided Design (13 citations). Takeshi Asahi has collaborated with scholars based in Chile, Japan and France. Frequent co-authors include Jaime H. Ortega, Rodrigo Lecaros, Gonzalo Rojas, Marcelo Gálvez, Kenichi Yoshikawa, Takatoshi Ichino, Konstantin Agladze, Nobuyuki Magome, Hiroyuki Kitahata and Orietta Echávarri. Their work appears in journals such as The Journal of Physical Chemistry C, Drugs and Lecture notes in computer science.
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.