Longyu Ma

1.1k citations
25 papers · 715 indexed · 1 hit paper · h-index 6

Longyu Ma

21 papers receiving 634 citations

Hit Papers

Efficient Iris Recognition by Characterizing Key Local Va...6372004202620112018200400600

Peers

Longyu Ma
Comparison fields: 5 of 56
  • Signal Processing 622
  • Computer Vision and Pattern Recognition 330
  • Safety Research 119
  • Information Systems 304
  • Genetics 87
Replace Robert W. Ives with:
Robert W. Ives United States
Neil Yager Australia
Byung Jun Kang South Korea
Arun Ross United States
Yingzi Du United States
K. Kollreider Sweden
Zhaofeng He China
Robert Snelick United States
Jen‐Chun Lee Taiwan
Eryun Liu China
Longyu Ma relative to Robert W. Ives United States Robert W. Ives's profile →
Citations per field
00.5×3.1×
Robert W. Ives · 1×
Citations per year

Countries citing papers authored by Longyu Ma

Since Specialization
Citations

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

Fields of papers citing papers by Longyu Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 21 scholars most cited alongside Longyu Ma, 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 Longyu Ma Line = papers co-authored together Longyu Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20252
4 202410
5 20244
6 20241
7 20242
8 20241
9 20241
10 20240
11 20240
12 20223
13 20213
14 20213
15 20203
16 20203
17 20201
18 201913
19 20193
20
Efficient Iris Recognition by Characterizing Key Local Variationsbreakdown →
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About Longyu Ma

Longyu Ma is a scholar working on Signal Processing, Computer Networks and Communications, Computer Vision and Pattern Recognition, Media Technology and Industrial and Manufacturing Engineering, having authored 25 papers that have together received 715 indexed citations. Recurring topics across this work include DNA and Biological Computing (6 papers), Error Correcting Code Techniques (6 papers), Biometric Identification and Security (5 papers), CCD and CMOS Imaging Sensors (3 papers), Cooperative Communication and Network Coding (3 papers), Advanced Wireless Communication Techniques (3 papers), Cellular Automata and Applications (3 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Signal Processing (622 citations), Computer Vision and Pattern Recognition (330 citations), Safety Research (119 citations), Information Systems (304 citations) and Genetics (87 citations). Longyu Ma has collaborated with scholars based in New Zealand, China and Luxembourg. Frequent co-authors include Yunlong Wang, Tieniu Tan, David Zhang, Chiu‐Wing Sham, Jing Sun, Symeon Chatzinotas, Thang X. Vu, Arsham Mostaani, Yuting Xie and Guolong Liang. Their work appears in journals such as IEEE Access, IEEE Wireless Communications Letters, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Circuits & Systems II Express Briefs and IEEE Transactions on Image Processing.

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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