Liang Bai

2.3k total citations
100 papers, 1.6k citations indexed

About

Liang Bai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Liang Bai has authored 100 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Artificial Intelligence, 32 papers in Computer Vision and Pattern Recognition and 16 papers in Signal Processing. Recurrent topics in Liang Bai's work include Advanced Clustering Algorithms Research (27 papers), Face and Expression Recognition (14 papers) and Data Management and Algorithms (11 papers). Liang Bai is often cited by papers focused on Advanced Clustering Algorithms Research (27 papers), Face and Expression Recognition (14 papers) and Data Management and Algorithms (11 papers). Liang Bai collaborates with scholars based in China, United Kingdom and Hong Kong. Liang Bai's co-authors include Jiye Liang, Fuyuan Cao, Chuangyin Dang, Yike Guo, Xueqi Cheng, Huawei Shen, Xian Yang, Deyu Li, Dexian Huang and Yongheng Jiang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Industrial & Engineering Chemistry Research.

In The Last Decade

Liang Bai

91 papers receiving 1.5k citations

Peers

Liang Bai
Comparison fields: 5 of 139
  • Artificial Intelligence 1.1k
  • Computer Vision and Pattern Recognition 477
  • Information Systems 283
  • Signal Processing 237
  • Statistical and Nonlinear Physics 209
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Qinbao Song China
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Mohammad‐Reza Feizi‐Derakhshi Iran
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Hamïd Parvïn Iran View profile →
Citations per field, relative to Liang Bai
Liang Bai · 1×
Citations per year, relative to Liang Bai
Liang Bai · 1×

Countries citing papers authored by Liang Bai

Since Specialization
Citations

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

Fields of papers citing papers by Liang Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Liang Bai. A scholar is included among the top collaborators of Liang Bai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liang Bai. Liang Bai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 1
4 3
5 2
6 5
7 1
8 14
9 4
10 2
11 2
12 2
13 46
14 8
15
Sparse Subspace Clustering with Entropy-Norm
9
16 13
17 30
18
Damping SINS algorithm based on outer position
3
19
Research of Multi-Threaded Technology on Elevator Remote Monitoring System
1
20
Automatic Audio Classification and Segmentation for Soccer Video Structuring
0

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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