Citations per year, relative to Sei‐ichiro Kamata Sei‐ichiro Kamata (= 1×)
peers
M. Petrou
Countries citing papers authored by Sei‐ichiro Kamata
Since
Specialization
Citations
This map shows the geographic impact of Sei‐ichiro Kamata'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 Sei‐ichiro Kamata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sei‐ichiro Kamata more than expected).
Fields of papers citing papers by Sei‐ichiro Kamata
This network shows the impact of papers produced by Sei‐ichiro Kamata. 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 Sei‐ichiro Kamata. The network helps show where Sei‐ichiro Kamata may publish in the future.
Co-authorship network of co-authors of Sei‐ichiro Kamata
This figure shows the co-authorship network connecting the top 25 collaborators of Sei‐ichiro Kamata.
A scholar is included among the top collaborators of Sei‐ichiro Kamata 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 Sei‐ichiro Kamata. Sei‐ichiro Kamata is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kamata, Sei‐ichiro, et al.. (2017). Face recognition via deep sparse graph neural networks.. Durham Research Online (Durham University).1 indexed citations
7.
Zhang, Qieshi & Sei‐ichiro Kamata. (2011). Manifold learning based on multi-feature for road-sign recognition. Society of Instrument and Control Engineers of Japan. 1143–1146.1 indexed citations
8.
Kamata, Sei‐ichiro, et al.. (2011). Raindrop removal from in-vehicle camera images based on matching adjacent frames. IEICE Technical Report; IEICE Tech. Rep.. 110(421). 227–232.1 indexed citations
Kamata, Sei‐ichiro, et al.. (2008). An automatic image-map alignment algorithm based on mutual information and Hilbert scan. European Signal Processing Conference. 1–5.
12.
Kamata, Sei‐ichiro, et al.. (2007). Video Lossless Compression Based on 3-Dimensional Prediction Using Spatio-Temporal Gradients. IEICE Technical Report; IEICE Tech. Rep.. 107(358). 109–113.1 indexed citations
13.
Kamata, Sei‐ichiro, et al.. (2006). A Gradient Based Predictive Coding for Lossless Image Compression(Image Processing and Video Processing). IEICE Transactions on Information and Systems. 89(7). 2250–2256.1 indexed citations
Kamata, Sei‐ichiro, et al.. (2002). Lossless Compression Method for Color Document Images. IEICE Transactions on Information and Systems. 85(4). 794.1 indexed citations
Kamata, Sei‐ichiro, Richard O. Eason, & Eiji Kawaguchi. (1993). Implementation of the Hilbert scanning algorithm and its application to data compression. IEICE Transactions on Information and Systems. 420–428.17 indexed citations
18.
Kamata, Sei‐ichiro, Richard O. Eason, & Eiji Kawaguchi. (1993). An Implementation of the Hilbert Scanning Algorithm and Its Application to Data Compression (Special Issue on Image Processing and Understanding). IEICE Transactions on Information and Systems. 76(4). 420–428.3 indexed citations
19.
Kamata, Sei‐ichiro, et al.. (1993). A Computation of Hilbert's Space-Filling Curves in N Dimensional Space. Transactions of the Institute of Electronics, Information and Communication Engineers. 76(3). 797–801.2 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.