Zhen-Liang Ni

794 citations
18 papers · 266 indexed · h-index 9

Zhen-Liang Ni

17 papers receiving 264 citations

Peers

Zhen-Liang Ni
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 109
  • Health Informatics 5
  • Biomedical Engineering 112
  • Cognitive Neuroscience 38
  • Surgery 85
Replace Abouzar Eslami with:
Abouzar Eslami Germany
Dante De Nigris Canada
Chenbin Ma China
Verónica García‐Vázquez Spain
Tobias Wissel Germany
Thiago Moraes Brazil
John Galeotti United States
Sepideh Hatamikia Austria
Olivier Pauly Germany
Su Huang Singapore
Zhen-Liang Ni relative to Abouzar Eslami Germany Abouzar Eslami's profile →
Citations per field
00.5×1.5×
Abouzar Eslami · 1×
Citations per year

Countries citing papers authored by Zhen-Liang Ni

Since Specialization
Citations

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

Fields of papers citing papers by Zhen-Liang Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhen-Liang Ni. 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 Zhen-Liang Ni. The network helps show where Zhen-Liang Ni may publish in the future.

Co-authorship network

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

All Works

18 of 18 papers shown
#Work
1 20240
2 20237
3 20224
4 20221
5 20227
6 20218
7 202132
8 202120
9 20213
10 20216
11 202040
12 202036
13 202014
14 202010
15 202026
16 20204
17 201942
18 20166

About Zhen-Liang Ni

Zhen-Liang Ni is a scholar working on Oral Surgery, Computer Vision and Pattern Recognition, Biomedical Engineering, Industrial and Manufacturing Engineering and Human-Computer Interaction, having authored 18 papers that have together received 266 indexed citations. Recurring topics across this work include Surgical Simulation and Training (8 papers), Anatomy and Medical Technology (5 papers), Medical Imaging and Analysis (4 papers), Medical Image Segmentation Techniques (3 papers), Advanced Neural Network Applications (3 papers), Advanced X-ray and CT Imaging (3 papers), Dental Radiography and Imaging (2 papers) and EEG and Brain-Computer Interfaces (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (109 citations), Health Informatics (5 citations), Biomedical Engineering (112 citations), Cognitive Neuroscience (38 citations) and Surgery (85 citations). Zhen-Liang Ni has collaborated with scholars based in China, Macao and Finland. Frequent co-authors include Zeng‐Guang Hou, Gui‐Bin Bian, Xiao-Hu Zhou, Xiao‐Liang Xie, Yan-Jie Zhou, Guan-An Wang, Zhen Li, Zhijie Fang, Ruiqi Li and Sheng Chen. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Medical Imaging, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Cybernetics and Medical Image Analysis.

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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