Hideaki Kimata

1.1k total citations
99 papers, 741 citations indexed

About

Hideaki Kimata is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology. According to data from OpenAlex, Hideaki Kimata has authored 99 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Computer Vision and Pattern Recognition, 38 papers in Signal Processing and 14 papers in Media Technology. Recurrent topics in Hideaki Kimata's work include Advanced Vision and Imaging (44 papers), Video Coding and Compression Technologies (36 papers) and Image and Video Quality Assessment (14 papers). Hideaki Kimata is often cited by papers focused on Advanced Vision and Imaging (44 papers), Video Coding and Compression Technologies (36 papers) and Image and Video Quality Assessment (14 papers). Hideaki Kimata collaborates with scholars based in Japan, United States and Taiwan. Hideaki Kimata's co-authors include Shinya Shimizu, Yoshiyuki Yashima, Kazuto Kamikura, Dan Mikami, M. Kitahara, Mariko Isogawa, Kosuke Takahashi, Toshiaki Fujii, Tomohiro Yendo and M. Tanimoto and has published in prestigious journals such as IEEE Access, Surface Science and International Journal of Computer Vision.

In The Last Decade

Hideaki Kimata

84 papers receiving 701 citations

Peers

Hideaki Kimata
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 523
  • Signal Processing 278
  • Genetics 84
  • Media Technology 69
  • Human-Computer Interaction 59
Replace L. L. Cheng with:
L. L. Cheng Hong Kong
André Anjos Switzerland
Hongyu Li China
Akira Kubota Japan
Hai Lin China
Dongge Li United States
Jeremy Dawson United States
Luuk Spreeuwers Netherlands
Charles Poynton United Kingdom
L. L. Cheng Hong Kong View profile →
Citations per field, relative to Hideaki Kimata
Hideaki Kimata · 1×
Citations per year, relative to Hideaki Kimata
Hideaki Kimata · 1×

Countries citing papers authored by Hideaki Kimata

Since Specialization
Citations

This map shows the geographic impact of Hideaki Kimata'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 Kimata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideaki Kimata more than expected).

Fields of papers citing papers by Hideaki Kimata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hideaki Kimata. 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 Kimata. The network helps show where Hideaki Kimata may publish in the future.

Co-authorship network of co-authors of Hideaki Kimata

This figure shows the co-authorship network connecting the top 25 collaborators of Hideaki Kimata. A scholar is included among the top collaborators of Hideaki Kimata 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 Kimata. Hideaki Kimata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 0
4 3
5 2
6 8
7 1
8 0
9 1
10
View synthesis motion estimation for multiview distributed video coding
2
11 23
12
A Proposal on Multi-view Video Capture Encoding System
1
13
Adaptive Filtering in View Synthesis Prediction for Multiview Video Coding
2
14 1
15
0
16 23
17
1
18 4
19 2
20 14

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.

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