Ling Xiao

987 citations
35 papers · 640 indexed · h-index 11
Topics
Industrial Vision Systems and Defect Detection (9 papers)Infrastructure Maintenance and Monitoring (4 papers)Advanced Neural Network Applications (4 papers)
Partner nations
ChinaJapanHong Kong

In The Last Decade

Ling Xiao

30 papers receiving 617 citations

Peers

Ling Xiao
Comparison fields: 5 of 98
  • Artificial Intelligence 204
  • Computer Vision and Pattern Recognition 162
  • Industrial and Manufacturing Engineering 143
  • Mechanical Engineering 116
  • Plant Science 97
Replace Quan Yu with:
Quan Yu China
Hao Dong China
Chang Huang China
Jinan Gu China
Lida Li China
Teerath Kumar Ireland
Antoni Grau Spain
Ebubekir Koç Türkiye
Jacek Naruniec Poland
Fangyun Wei China
Ling Xiao relative to Quan Yu China Quan Yu's profile →
Citations per field
00.5×6.4×
Quan Yu · 1×
Citations per year

Countries citing papers authored by Ling Xiao

Since Specialization
Citations

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

Fields of papers citing papers by Ling Xiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Xiao

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Xiao. A scholar is included among the top collaborators of Ling Xiao 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 Ling Xiao. Ling Xiao 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
#WorkIndexed citations
1 0
2 0
3 1
4 0
5 27
6 9
7 1
8 1
9 2
10 0
11 4
12 67
13 38
14 7
15 5
16 2
17 7
18
Can Chinese web pages be classified with english data
1
19 48
20 26

About Ling Xiao

Ling Xiao is a scholar working on Industrial and Manufacturing Engineering, General Engineering and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 640 indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (9 papers), Infrastructure Maintenance and Monitoring (4 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (143 citations), Computer Vision and Pattern Recognition (162 citations) and Artificial Intelligence (204 citations). Ling Xiao has collaborated with scholars based in China, Japan and Hong Kong. Frequent co-authors include Bo Wu, Gui-Rong Xue, Yong Yu, Qiang Yang, Youmin Hu, Wenyuan Dai, Yuanshen Zhao, Chengliang Liu, Liang Gong and Mingyuan Lu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and Neurocomputing.

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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