Kuan-Ting Lai

1.1k citations
32 papers · 677 · 1 hit paper · h-index 12

Impact in

Papers in

Kuan-Ting Lai

29 papers receiving 635 citations

Hit Papers

Deep learning for brain age estimation: A systematic review 2023 · 84 citations
840+1+2Years since publication255075

Peers

Kuan-Ting Lai
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 243
  • Computer Networks and Communications 253
  • Artificial Intelligence 152
  • Neurology 32
  • Health Informatics 5
Replace Salabat Khan with:
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Abdulaziz S. Almazyad Saudi Arabia
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Syed Muzamil Basha India
Amal Al‐Rasheed Saudi Arabia
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Citations per field
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Citations per year

Countries citing papers authored by Kuan-Ting Lai

Since Specialization
Citations

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

Fields of papers citing papers by Kuan-Ting Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuan-Ting Lai. 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 Kuan-Ting Lai. The network helps show where Kuan-Ting Lai may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999202
2 201485
3
Deep learning for brain age estimation: A systematic review
Hit paper breakdown →
202384
4 201148
5 200847
6 201346
7 200622
8 202118
9 201517
10 202217
11 201814
12 202111
13 20199
14 20178
15 20187
16 20206
17 20215
18 20225
19 20215
20 20225

About Kuan-Ting Lai

Kuan-Ting Lai is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Information Systems and Social Psychology, having authored 32 papers that have together received 677 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (10 papers), Advanced Neural Network Applications (7 papers), Human Pose and Action Recognition (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Image Enhancement Techniques (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Crime Patterns and Interventions (2 papers) and IoT and Edge/Fog Computing (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (243 citations), Computer Networks and Communications (253 citations), Artificial Intelligence (152 citations), Neurology (32 citations) and Health Informatics (5 citations). Kuan-Ting Lai has collaborated with scholars based in Taiwan, United States and India. Frequent co-authors include Mary Baker, Ming-Syan Chen⋆, Shih‐Fu Chang, Felix X. Yu, Michal Feldman, Li Zhang, Chaur‐Heh Hsieh, Yudong Zhang, Dong Liu and Iman Beheshti. Their work appears in journals such as IEEE Systems Journal, Information Fusion, Applied Sciences, IEEE Internet of Things Journal and IEEE Transactions on Image Processing.

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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