Nobuyuki Otsu
About
In The Last Decade
Nobuyuki Otsu
67 papers receiving 30.3k citations
Hit Papers
Peers
Comparison fields: 5 of 223
- Computer Vision and Pattern Recognition 12.5k
- Media Technology 4.4k
- Artificial Intelligence 3.5k
- Radiology, Nuclear Medicine and Imaging 3.5k
- Biomedical Engineering 3.5k
Countries citing papers authored by Nobuyuki Otsu
This map shows the geographic impact of Nobuyuki Otsu'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 Nobuyuki Otsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nobuyuki Otsu more than expected).
Fields of papers citing papers by Nobuyuki Otsu
This network shows the impact of papers produced by Nobuyuki Otsu. 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 Nobuyuki Otsu. The network helps show where Nobuyuki Otsu may publish in the future.
Co-authorship network of co-authors of Nobuyuki Otsu
This figure shows the co-authorship network connecting the top 25 collaborators of Nobuyuki Otsu. A scholar is included among the top collaborators of Nobuyuki Otsu 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 Nobuyuki Otsu. Nobuyuki Otsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Partial Matching Method using Spatio-temporal Regularized Canonical Correlation Analysis | 1 |
| 2 | 0 | |
| 3 | 28 | |
| 4 | 8 | |
| 5 | A Method of Motion Evaluation using Time Weights and External Criteria | 1 |
| 6 | Moving Object Detection by Using Markov Random Field Model | 1 |
| 7 | 1 | |
| 8 | Realtime Motion Recognition by using CHLAC feature and Grid Computing | 0 |
| 9 | High Precision Gait Recognition Using Large Scale PC Cluster | 1 |
| 10 | Unsupervised Abnormality Detection in Video Surveillance | 38 |
| 11 | A New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis | 7 |
| 12 | A Learning-Based Quantization: Unsupervised Estimation of the Model Parameters | 18 |
| 13 | A learning-based jam session system that imitates a player's personality model | 13 |
| 14 | Learning-Based Jam Session System for A Guitar Trio | 4 |
| 15 | 10 | |
| 16 | 6 | |
| 17 | Active agent oriented multimodal interface system | 19 |
| 18 | Toward flexible intelligence: MITI's new program of real world computing | 6 |
| 19 | A New Scheme for Practical Flexible and Intelligent Vision Systems | 162 |
| 20 | A Threshold Selection Method from Gray-Level Histograms breakdown → | 31205 |
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.