Kaili Wang

485 total citations
29 papers, 302 citations indexed

About

Kaili Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Kaili Wang has authored 29 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Media Technology. Recurrent topics in Kaili Wang's work include Handwritten Text Recognition Techniques (6 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Image Retrieval and Classification Techniques (3 papers). Kaili Wang is often cited by papers focused on Handwritten Text Recognition Techniques (6 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Image Retrieval and Classification Techniques (3 papers). Kaili Wang collaborates with scholars based in China, Belgium and Taiwan. Kaili Wang's co-authors include Weisheng Li, Junwei Han, Bin Xiao, Yaohua Yi, Xiuli Bi, Ke Dong, Faliang Huang, Jiang Wu, Qi Wang and Ziwei Tang and has published in prestigious journals such as IEEE Access, Neurocomputing and Applied Soft Computing.

In The Last Decade

Kaili Wang

23 papers receiving 296 citations

Peers

Kaili Wang
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 137
  • Artificial Intelligence 58
  • Media Technology 30
  • Plant Science 28
  • Biomedical Engineering 17
Replace Teekam Singh with:
Teekam Singh India
S. Margret Anouncia India
Sachin Sharma India
Nor Azman Ismail Malaysia
Insaf Adjabi Algeria
Flávio de Barros Vidal Brazil
Reza Fuad Rachmadi Indonesia
Dim P. Papadopoulos United States
M. Rahmat Widyanto Indonesia
Teekam Singh India View profile →
Citations per field, relative to Kaili Wang
Kaili Wang · 1×
Citations per year, relative to Kaili Wang
Kaili Wang · 1×

Countries citing papers authored by Kaili Wang

Since Specialization
Citations

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

Fields of papers citing papers by Kaili Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaili Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Kaili Wang. A scholar is included among the top collaborators of Kaili Wang 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 Kaili Wang. Kaili Wang 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 1
2 1
3 0
4 0
5 0
6 0
7 3
8 2
9 17
10 0
11 1
12 7
13 46
14 12
15 21
16 57
17
Integrated unpaired appearance-preserving shape translation across domains.
2
18 4
19
BEYOND FLOW EXPERIENCE: LEARNERS’ POSITIVE AND NEGATIVE EMOTIONS RELATED TO COMPUTER-BASED INSTRUCTION
1
20
DDL translation teaching based on bilingual corpora of tourism texts : an application
1

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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