Pan Hui

152 papers receiving 2.2k citations

Pan Hui's Hit Papers

A Multi-Stream Feature Fusion Approach for Traffic Prediction 2020 · 221 citations
2210+2+4Years since publication50100150200

Peers

Pan Hui
Comparison fields: 5 of 141
  • Transportation 295
  • Human-Computer Interaction 210
  • Computer Networks and Communications 685
  • Computer Vision and Pattern Recognition 444
  • Computer Science Applications 87
Replace Stefan Poslad with:
Stefan Poslad United Kingdom
George Roussos United Kingdom
Marco Roccetti Italy
Yu Xiao Finland
Marco Mamei Italy
Xia Zhou United States
Runhe Huang Japan
Rajesh Krishna Balan Singapore
Xianzhi Wang Australia
Zhu Wang China
Pan Hui relative to Stefan Poslad United Kingdom Stefan Poslad's profile →
Citations per field
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Stefan Poslad · 1×
Citations per year

Countries citing papers authored by Pan Hui

Since Specialization
Citations

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

Fields of papers citing papers by Pan Hui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 174 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Multi-Stream Feature Fusion Approach for Traffic Prediction
Hit paper breakdown →
2020221
2 2014106
3 2006101
4 201374
5 202272
6 201861
7 201757
8 201153
9 202053
10 201850
11 202248
12 202043
13 201539
14 201439
15 202337
16 201834
17 202234
18 202134
19 202432
20 201930

About Pan Hui

Pan Hui is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Human-Computer Interaction, Information Systems and Artificial Intelligence, having authored 174 papers that have together received 2.2k indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (23 papers), Opportunistic and Delay-Tolerant Networks (16 papers), IoT and Edge/Fog Computing (15 papers), Augmented Reality Applications (15 papers), Human Mobility and Location-Based Analysis (15 papers), Complex Network Analysis Techniques (14 papers), Caching and Content Delivery (14 papers) and Vehicular Ad Hoc Networks (VANETs) (9 papers). The work is most often cited by research in Transportation (295 citations), Human-Computer Interaction (210 citations), Computer Networks and Communications (685 citations), Computer Vision and Pattern Recognition (444 citations) and Computer Science Applications (87 citations). Pan Hui has collaborated with scholars based in Hong Kong, China and Finland. Frequent co-authors include Yong Li, Bo Han, Wenxiao Zhang, Depeng Jin, Sasu Tarkoma, Tristan Braud, Tong Li, Dimitris Chatzopoulos, Lik‐Hang Lee and Ling Wang. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, ACM Computing Surveys, ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Mobile Computing and IEEE Transactions on Visualization and Computer Graphics.

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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