Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Matched-Transmission Technique for Channels With Intersymbol Interference
Citations per year, relative to Hiroshi Harashima Hiroshi Harashima (= 1×)
peers
Maria G. Martini
Countries citing papers authored by Hiroshi Harashima
Since
Specialization
Citations
This map shows the geographic impact of Hiroshi Harashima'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 Hiroshi Harashima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroshi Harashima more than expected).
Fields of papers citing papers by Hiroshi Harashima
This network shows the impact of papers produced by Hiroshi Harashima. 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 Hiroshi Harashima. The network helps show where Hiroshi Harashima may publish in the future.
Co-authorship network of co-authors of Hiroshi Harashima
This figure shows the co-authorship network connecting the top 25 collaborators of Hiroshi Harashima.
A scholar is included among the top collaborators of Hiroshi Harashima 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 Hiroshi Harashima. Hiroshi Harashima is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Harashima, Hiroshi, et al.. (2000). A Classification of Cerebral Disease by Using Face Image Synthesis. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 83(9). 1853–1859.
3.
Naemura, Takeshi, Masahide Kaneko, & Hiroshi Harashima. (1999). Compression and Representation of 3-D Images. IEICE Transactions on Information and Systems. 82(3). 558–567.15 indexed citations
4.
Hanaoka, Goichiro, Masahide Kaneko, & Hiroshi Harashima. (1997). Facial Caricature by Computer Based on the Style of Individual Human Caricaturist. Transactions of the Institute of Electronics, Information and Communication Engineers. 80(8). 2110–2118.3 indexed citations
5.
Saito, Takahiro, et al.. (1996). Interactive model-based coding of facial image sequence with a new motion detection algorithm. IEICE Transactions on Communications. 1474–1482.3 indexed citations
6.
Kaneko, Masahide, et al.. (1996). Interactive Model-based Coding for Multimedia E-mail Environment. 2. 663–668.2 indexed citations
7.
Yamada, Hiroshi, et al.. (1995). Robot and Human Communication - Proceedings of the IEEE International Workshop.2 indexed citations
8.
Fujii, Toshiaki & Hiroshi Harashima. (1994). Data Compression and Interpolation of Multi-View Image Set. IEICE Transactions on Information and Systems. 987–995.8 indexed citations
9.
Morishima, Shigeo, et al.. (1994). Expression analysis/synthesis system based on emotion space constructed by multilayered neural network. Systems and Computers in Japan. 25(13). 95–107.25 indexed citations
10.
Harashima, Hiroshi. (1994). Special Issue on Networked Reality. IEICE Transactions on Information and Systems. 77(12). 1317.7 indexed citations
11.
Morikawa, Hiroyuki, Eiji Kondo, & Hiroshi Harashima. (1993). 3D Facial Modelling for Model-Based Coding (Special Issue on Next Generation Visual Telecommunication and Broadcasting). IEICE Transactions on Communications. 76(6). 626–633.2 indexed citations
12.
Morikawa, Hiroyuki & Hiroshi Harashima. (1993). Incremental Segmentation of Moving Pictures-An Analysis by Synthesis Approach (Special Issue on Image Processing and Understanding). IEICE Transactions on Information and Systems. 76(4). 446–453.2 indexed citations
13.
Kishino, Fumio, et al.. (1993). Toward the New Era of Visual Communication (Special Issue on Next Generation Visual Telecommunication and Broadcasting). IEICE Transactions on Communications. 76(6). 577–591.6 indexed citations
14.
Harashima, Hiroshi, et al.. (1992). Model-Based/Waveform Hybrid Coding for Low-Rate Transmission of Facial Images. IEICE Transactions on Communications. 377–384.7 indexed citations
15.
Morishima, Shigeo & Hiroshi Harashima. (1992). Image synthesis and editing system for a multi-media human interface with speaking head. International Conference on Image Processing. 270–273.3 indexed citations
16.
Harashima, Hiroshi & Fumio Kishino. (1991). Intelligent Image Coding and Communications with Realistic Sensations --Recent Trends--. IEICE Transactions on Communications. 1582–1592.25 indexed citations
17.
Harashima, Hiroshi, et al.. (1990). Analysis and Synthesis of Facial Image Sequence in Knowledge-Based Image Coding. 3. 80–84.1 indexed citations
18.
Harashima, Hiroshi, Kiyoharu Aizawa, & Takahiro Saito. (1989). Model-Based Analysis Synthesis Coding of Videotelephone Images--Conception and Basic Study of Intelligent Image Coding--. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 452–459.24 indexed citations
19.
Arakawa, Kaoru & Hiroshi Harashima. (1987). Optimization of a Piecewise Linear Digital Filter. International Symposium on Circuits and Systems. 73–78.2 indexed citations
20.
Arakawa, Kaoru, Hiroshi Harashima, & Hiroshi Miyakawa. (1983). STATISTICAL ANALYSIS OF epsilon -SEPARATING NONLINEAR DIGITAL FILTERS.. Electronics and Communications in Japan. 6(1). 10–18.1 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.