Liangcai Gao

2.3k citations
96 papers · 1.1k indexed · h-index 20

Liangcai Gao

89 papers receiving 1.0k citations

Peers

Liangcai Gao
Comparison fields: 5 of 122
  • Computer Vision and Pattern Recognition 536
  • Biological Psychiatry 66
  • Artificial Intelligence 359
  • Computational Theory and Mathematics 175
  • Behavioral Neuroscience 38
Replace Qi Guo with:
Qi Guo China
Cong Lei China
Justin Bedő Australia
Candong Li China
Ahmet Saçan United States
Subhadip Basu India
Vincenzo De Florio Belgium
Yu Fu China
Kate Ching‐Ju Lin Taiwan
Jinyan Wang China
Liangcai Gao relative to Qi Guo China Qi Guo's profile →
Citations per field
00.5×9.2×
Qi Guo · 1×
Citations per year

Countries citing papers authored by Liangcai Gao

Since Specialization
Citations

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

Fields of papers citing papers by Liangcai Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20251
4 20240
5 20240
6 20222
7 20226
8 201967
9 20183
10
[Prevalence and risk factors of chronic mountain sickness in Pamirs plateau].
20181
11 201811
12 201720
13 201726
14
The Math Retrieval System of ICST for NTCIR-12 MathIR Task.
20167
15
ICST Math Retrieval System for NTCIR-11 Math-2 Task
20146
16 201425
17 20141
18 201477
19 201128
20 200910

About Liangcai Gao

Liangcai Gao is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Biological Psychiatry, having authored 96 papers that have together received 1.1k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (31 papers), Mathematics, Computing, and Information Processing (19 papers), Image Retrieval and Classification Techniques (16 papers), Video Analysis and Summarization (11 papers), Advanced Image and Video Retrieval Techniques (11 papers), Web Data Mining and Analysis (10 papers), Topic Modeling (9 papers) and Image Processing and 3D Reconstruction (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (536 citations), Biological Psychiatry (66 citations) and Artificial Intelligence (359 citations). Liangcai Gao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhi Tang, Zhuoren Jiang, Xiaohan Yi, Xiaozhong Liu, Xiaofan Lin, Xiaoyan Lin, Xiaode Zhang, Yongtao Wang, Ke Yuan and Limin Xiao. Their work appears in journals such as Neuroreport, International Journal on Document Analysis and Recognition (IJDAR), Biochemical Pharmacology, Journal of Neuroinflammation and Nature Biotechnology.

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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