Ken Cai

50 papers receiving 787 citations

Ken Cai's Hit Papers

A Short-Term Traffic Flow Prediction Model Based on an Improved Gate Recurrent Unit Neural Network 2021 · 167 citations
1670+1+3Years since publication50100150

Peers

Ken Cai
Comparison fields: 5 of 116
  • Transportation 93
  • Building and Construction 135
  • Computer Vision and Pattern Recognition 157
  • Computer Networks and Communications 164
  • Media Technology 61
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Qiang Niu China
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Ken Cai relative to Qiang Niu China Qiang Niu's profile →
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Countries citing papers authored by Ken Cai

Since Specialization
Citations

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

Fields of papers citing papers by Ken Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Short-Term Traffic Flow Prediction Model Based on an Improved Gate Recurrent Unit Neural Network
Hit paper breakdown →
2021167
2 202070
3 202169
4 202153
5 202050
6 202334
7 201633
8 202027
9 201922
10 201621
11 201221
12 201519
13 201919
14 201018
15 202017
16 201814
17 201914
18 201613
19 202011
20 202210

About Ken Cai

Ken Cai is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 51 papers that have together received 820 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (6 papers), Robotics and Sensor-Based Localization (5 papers), Traffic Prediction and Management Techniques (5 papers), IoT and Edge/Fog Computing (4 papers), Multi-Criteria Decision Making (4 papers), Augmented Reality Applications (4 papers), Wireless Body Area Networks (3 papers) and Remote-Sensing Image Classification (3 papers). The work is most often cited by research in Transportation (93 citations), Building and Construction (135 citations), Computer Vision and Pattern Recognition (157 citations), Computer Networks and Communications (164 citations) and Media Technology (61 citations). Ken Cai has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Wanneng Shu, Naixue Xiong, Qinyong Lin, Rongqian Yang, Huazhou Chen, Bohan Li, Qingjun Wang, Liang Qiao, Xiaoying Liang and Hongtao Wang. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Computer Communications, International Journal of Emerging Technologies in Learning (iJET), IEEE Access and International Journal of Advancements in Computing Technology.

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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