Chun‐Hsiang Chen

402 citations
15 papers · 250 · h-index 10

Impact in

Papers in

Chun‐Hsiang Chen

14 papers receiving 244 citations

Peers

Chun‐Hsiang Chen
Comparison fields: 5 of 74
  • Toxicology 21
  • Environmental Chemistry 44
  • Insect Science 33
  • Computer Networks and Communications 47
  • Artificial Intelligence 57
Replace J. W. Eaton with:
J. W. Eaton United States
Guanwen Li China
George Pallis Greece
Jiangning Wang China
Qiushi Yang China
Cheng Da China
Haoxiang Lin China
An Phan Germany
Giacinto Donvito Italy
Yu‐Ching Liu Taiwan
Chun‐Hsiang Chen relative to J. W. Eaton United States J. W. Eaton's profile →
Citations per field
00.5×10×15×19×
J. W. Eaton · 1×
Citations per year

Countries citing papers authored by Chun‐Hsiang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Chun‐Hsiang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun‐Hsiang Chen. 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 Chun‐Hsiang Chen. The network helps show where Chun‐Hsiang Chen may publish in the future.

Co-authors

The 21 scholars most cited alongside Chun‐Hsiang Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chun‐Hsiang Chen Line = papers co-authored together Chun‐Hsiang Chen links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 200850
2 202046
3 200540
4 202320
5 202018
6 201015
7 200615
8 201015
9 202013
10 201011
11 20102
12 20042
13 20092
14
Accumulated Polar Feature based Deep Learning with Channel Compensation Mechanism for Efficient Automatic Modulation Classification under Time varying Channels.
20201
15
A Comparative Study of "The International Educational Technology Conference" (IETC) and "The International Conference on Computers in Education" (ICCE): The Program, Essay Distribution, the Themes, and Research Methods
20120

About Chun‐Hsiang Chen

Chun‐Hsiang Chen is a scholar working on Computer Networks and Communications, Molecular Biology, Ecology, Electrical and Electronic Engineering and Artificial Intelligence, having authored 15 papers that have together received 250 indexed citations. Recurring topics across this work include Selenium in Biological Systems (2 papers), Advanced Wireless Communication Techniques (2 papers), Mollusks and Parasites Studies (2 papers), Advanced Data Storage Technologies (2 papers), Wireless Signal Modulation Classification (2 papers), Radar Systems and Signal Processing (2 papers), Error Correcting Code Techniques (2 papers) and Distributed and Parallel Computing Systems (2 papers). The work is most often cited by research in Toxicology (21 citations), Environmental Chemistry (44 citations), Insect Science (33 citations), Computer Networks and Communications (47 citations) and Artificial Intelligence (57 citations). Chun‐Hsiang Chen has collaborated with scholars based in Taiwan and United States. Frequent co-authors include An-Yeu Wu, Chuan‐Min Yen, Deng‐Fwu Hwang, Yung‐Hsiang Tsai, Li‐Yu Tsai, Lian-Chen Wang, Yuan‐Hsiou Chang, Shih‐Yu Wang, Chao‐Tung Yang and Shun‐Jen Chang. Their work appears in journals such as Parasitology Research, Microelectronic Engineering, ACS Nano, Acta Tropica and Redox Report.

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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