Koichi Niijima

525 total citations
61 papers, 309 citations indexed

About

Koichi Niijima is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Signal Processing. According to data from OpenAlex, Koichi Niijima has authored 61 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 14 papers in Computational Mechanics and 12 papers in Signal Processing. Recurrent topics in Koichi Niijima's work include Image and Signal Denoising Methods (15 papers), Computer Graphics and Visualization Techniques (12 papers) and 3D Shape Modeling and Analysis (10 papers). Koichi Niijima is often cited by papers focused on Image and Signal Denoising Methods (15 papers), Computer Graphics and Visualization Techniques (12 papers) and 3D Shape Modeling and Analysis (10 papers). Koichi Niijima collaborates with scholars based in Japan, Saudi Arabia and China. Koichi Niijima's co-authors include Shigeru Takano, Yoshihiro Okada, Y. Okada, Muhammad Hussain, Yoshio Tanaka, Katsunori Miyahara, Naoto Nakamura and Nobuhiro Ohta and has published in prestigious journals such as IEEE Transactions on Signal Processing, Mathematics of Computation and Neural Networks.

In The Last Decade

Koichi Niijima

55 papers receiving 287 citations

Peers

Koichi Niijima
Comparison fields: 5 of 53
  • Computer Vision and Pattern Recognition 150
  • Computational Mechanics 89
  • Numerical Analysis 74
  • Computational Theory and Mathematics 51
  • Computer Graphics and Computer-Aided Design 51
Replace Thomas Yu with:
Thomas Yu United States
Meie Fang China
Jamaludin Md. Ali Malaysia
A.J. Worsey United States
D. Gawley Australia
Azali Saudi Malaysia
Chih-Fan Chen United States
Marie‐Laurence Mazure France
Alok Kumar India
Thomas Yu United States View profile →
Citations per field, relative to Koichi Niijima
Koichi Niijima · 1×
Citations per year, relative to Koichi Niijima
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Countries citing papers authored by Koichi Niijima

Since Specialization
Citations

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

Fields of papers citing papers by Koichi Niijima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koichi Niijima

This figure shows the co-authorship network connecting the top 25 collaborators of Koichi Niijima. A scholar is included among the top collaborators of Koichi Niijima 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 Koichi Niijima. Koichi Niijima 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 1
2
Robust person authentication using dyadic wavelet filters learned by cosine-maximization
0
3 2
4 1
5 1
6 1
7 8
8 8
9
Personal identification by multiresolution analysis of lifting dyadic wavelets
1
10 2
11 2
12 1
13 1
14 2
15 5
16
Extraction of Subimages by Lifting Wavelet Filters
2
17 5
18 3
19 0
20 3

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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