Haijun Lin

94 papers receiving 896 citations

Peers

Haijun Lin
Comparison fields: 5 of 110
  • Electronic, Optical and Magnetic Materials 162
  • Industrial and Manufacturing Engineering 55
  • Water Science and Technology 76
  • Computer Vision and Pattern Recognition 113
  • Electrical and Electronic Engineering 276
Replace Cian O’Mathúna with:
Cian O’Mathúna Ireland
Hai Yang China
Helena G. Ramos Portugal
Jianguo Yang China
Hengliang Zhang China
Limin Zhang China
Xinxing Chen China
Yigang Wang China
Haijun Lin relative to Cian O’Mathúna Ireland Cian O’Mathúna's profile →
Citations per field
00.5×4.7×
Cian O’Mathúna · 1×
Citations per year

Countries citing papers authored by Haijun Lin

Since Specialization
Citations

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

Fields of papers citing papers by Haijun Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Haijun Lin, 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 Haijun Lin Line = papers co-authored together Haijun Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201991
2 201558
3 202253
4 202249
5 201840
6 202136
7 202228
8 202027
9 201426
10 202226
11 202023
12 202219
13 202019
14 202218
15 201618
16 201917
17 202415
18 202115
19
[Mahalanobis distance based hyperspectral characteristic discrimination of leaves of different desert tree species].
201413
20 202012

About Haijun Lin

Haijun Lin is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Control and Systems Engineering, Mechanical Engineering and Computer Vision and Pattern Recognition, having authored 105 papers that have together received 932 indexed citations. Recurring topics across this work include Analog and Mixed-Signal Circuit Design (11 papers), Transport Systems and Technology (11 papers), Water Quality Monitoring Technologies (11 papers), Water Quality Monitoring and Analysis (10 papers), Sensor Technology and Measurement Systems (10 papers), Advanced Steganography and Watermarking Techniques (6 papers), Fault Detection and Control Systems (5 papers) and Advanced Battery Technologies Research (5 papers). The work is most often cited by research in Electronic, Optical and Magnetic Materials (162 citations), Industrial and Manufacturing Engineering (55 citations), Water Science and Technology (76 citations), Computer Vision and Pattern Recognition (113 citations) and Electrical and Electronic Engineering (276 citations). Haijun Lin has collaborated with scholars based in China, Japan and Taiwan. Frequent co-authors include Houde Dai, Jianmin Li, Zhaosheng Teng, Yuxiang Yang, Tim C. Lueth, Rongrong Guo, Kai‐Da Xu, Fu Zhang, Jinfeng Zhu and Naixing Feng. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Measurement, IEEE Sensors Journal, Computers, materials & continua/Computers, materials & continua (Print) and International journal of agricultural and biological engineering.

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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