Hideaki Goto
About
In The Last Decade
Hideaki Goto
113 papers receiving 756 citations
Peers
Comparison fields: 5 of 111
- Computer Vision and Pattern Recognition 169
- Geophysics 159
- Oncology 90
- Molecular Biology 87
- Media Technology 80
Countries citing papers authored by Hideaki Goto
This map shows the geographic impact of Hideaki Goto'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 Hideaki Goto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideaki Goto more than expected).
Fields of papers citing papers by Hideaki Goto
This network shows the impact of papers produced by Hideaki Goto. 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 Hideaki Goto. The network helps show where Hideaki Goto may publish in the future.
Co-authorship network of co-authors of Hideaki Goto
This figure shows the co-authorship network connecting the top 25 collaborators of Hideaki Goto. A scholar is included among the top collaborators of Hideaki Goto 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 Hideaki Goto. Hideaki Goto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | Disruption-tolerant, Large-scale Wireless LAN Roaming Architecture for eduroam | 2 |
| 9 | 7 | |
| 10 | 3 | |
| 11 | Binary Tree-Based Accuracy-Keeping Clustering Using CDA for Very Fast Japanese Character Recognition | 0 |
| 12 | Wearable Reading Assistant Device for the Blind | 1 |
| 13 | 9 | |
| 14 | A Weighted Voting Method for Combining Multiple Character Recognition Engines | 1 |
| 15 | 2 | |
| 16 | Analysis and comparison of frequency features for scene text detection | 4 |
| 17 | Designing Efficient Hough Transform by Noise-Level Shaping | 1 |
| 18 | 3 | |
| 19 | An Algorithm for Reducing Text Line Candidates of Incorrect Orientation. | 1 |
| 20 | On the Efficient Sampling Interval of the Parameter in Hough Transform | 1 |
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.