Lingfen Sun

2.4k total citations
86 papers, 1.7k citations indexed

About

Lingfen Sun is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Lingfen Sun has authored 86 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 42 papers in Computer Networks and Communications and 32 papers in Signal Processing. Recurrent topics in Lingfen Sun's work include Image and Video Quality Assessment (45 papers), Video Coding and Compression Technologies (24 papers) and Network Traffic and Congestion Control (19 papers). Lingfen Sun is often cited by papers focused on Image and Video Quality Assessment (45 papers), Video Coding and Compression Technologies (24 papers) and Network Traffic and Congestion Control (19 papers). Lingfen Sun collaborates with scholars based in United Kingdom, Spain and China. Lingfen Sun's co-authors include Emmanuel Ifeachor, Asiya Khan, Emmanuel Jammeh, Is-Haka Mkwawa, Alcardo Alex Barakabitze, Luigi Atzori, Arslan Ahmad, Maria G. Martini, Saman Zadtootaghaj and Nabajeet Barman and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, Journal of Neurology Neurosurgery & Psychiatry and IEEE Access.

In The Last Decade

Lingfen Sun

83 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lingfen Sun United Kingdom 22 906 770 461 409 251 86 1.7k
Maria G. Martini United Kingdom 27 1.7k 1.9× 544 0.7× 658 1.4× 621 1.5× 234 0.9× 189 2.6k
Truong Cong Thang Japan 21 1.1k 1.2× 327 0.4× 702 1.5× 589 1.4× 256 1.0× 159 1.8k
Maria Torres Vega Belgium 16 574 0.6× 260 0.3× 221 0.5× 149 0.4× 111 0.4× 72 948
David Hands United Kingdom 11 639 0.7× 134 0.2× 274 0.6× 97 0.2× 176 0.7× 34 901
Miska M. Hannuksela Finland 27 2.8k 3.1× 398 0.5× 2.2k 4.9× 371 0.9× 424 1.7× 188 3.2k
Panos Nasiopoulos Canada 24 1.9k 2.1× 266 0.3× 1.1k 2.3× 277 0.7× 79 0.3× 238 2.4k
Hari Kalva United States 22 1.1k 1.2× 232 0.3× 684 1.5× 123 0.3× 142 0.6× 139 1.4k
Emmanuel Jammeh United Kingdom 15 294 0.3× 194 0.3× 137 0.3× 116 0.3× 83 0.3× 37 836
Yufei Ma China 20 3.0k 3.3× 122 0.2× 637 1.4× 1.1k 2.6× 319 1.3× 70 3.6k
Wai-Tian Tan United States 20 642 0.7× 962 1.2× 562 1.2× 478 1.2× 124 0.5× 88 1.5k

Countries citing papers authored by Lingfen Sun

Since Specialization
Citations

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

Fields of papers citing papers by Lingfen Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingfen Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Lingfen Sun. A scholar is included among the top collaborators of Lingfen Sun 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 Lingfen Sun. Lingfen Sun 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
1.
2.
Mkwawa, Is-Haka, et al.. (2023). Quality-of-Things Based Machine Learning for the MIoT Applications. 50. 1–5.
3.
Jammeh, Emmanuel, et al.. (2021). Robust EEG Based Biomarkers to Detect Alzheimer’s Disease. Brain Sciences. 11(8). 1026–1026. 23 indexed citations
4.
Mkwawa, Is-Haka, et al.. (2020). How to Manage Multimedia Traffic: Based on QoE or QoT?. ZTE communications. 16(3). 23–29. 2 indexed citations
5.
Barakabitze, Alcardo Alex, Lingfen Sun, Is-Haka Mkwawa, & Emmanuel Ifeachor. (2018). A Novel QoE-Centric SDN-Based Multipath Routing Approach for Multimedia Services over 5G Networks. PEARL (University of Plymouth). 1–7. 37 indexed citations
6.
Mkwawa, Is-Haka, et al.. (2018). Optimum Encoding Approaches on Video Resolution Changes: A Comparative Study. ECS Journal of Solid State Science and Technology (The Electrochemical Society). 2014. 1003–1007. 1 indexed citations
7.
Hu, Shenghong, Lingfen Sun, Chunxia Xiao, & Chao Gui. (2017). Semantic-aware adaptation scheme for soccer video over MPEG-DASH. PEARL (University of Plymouth). 7. 493–498. 4 indexed citations
8.
Ghita, Bogdan, et al.. (2017). QoE-driven video enhancements in wireless networks through predictive packet drops. 355–361. 3 indexed citations
9.
Liberal, Fidel, José Oscar Fajardo, George Lyberopoulos, et al.. (2013). User requirements for future wideband critical communications. 341–348. 1 indexed citations
10.
Sun, Lingfen, et al.. (2013). Encoding and video content based HEVC video quality prediction. Multimedia Tools and Applications. 74(11). 3715–3738. 8 indexed citations
11.
Goudarzi, Mohammad, Lingfen Sun, & Emmanuel Ifeachor. (2011). Modelling Speech Quality for NB and WB SILK Codec for VoIP Applications. 42–47. 10 indexed citations
12.
Khan, Asiya, Lingfen Sun, Emmanuel Ifeachor, et al.. (2010). Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks. International Journal of Digital Multimedia Broadcasting. 2010. 1–17. 32 indexed citations
13.
Khan, Asiya, Lingfen Sun, Emmanuel Ifeachor, José Oscar Fajardo, & Fidel Liberal. (2010). Video Quality Prediction Model for H.264 Video over UMTS Networks and Their Application in Mobile Video Streaming. Zenodo (CERN European Organization for Nuclear Research). 1–5. 32 indexed citations
14.
Khan, Asiya, Lingfen Sun, Emmanuel Jammeh, & Emmanuel Ifeachor. (2010). Quality of experience-driven adaptation scheme for video applications over wireless networks. IET Communications. 4(11). 1337–1347. 131 indexed citations
15.
Khan, Asiya, Lingfen Sun, Emmanuel Jammeh, & Emmanuel Ifeachor. (2009). Content classification-based and QoE-driven video send bitrate adaptation scheme. 6 indexed citations
16.
Mkwawa, Is-Haka, Emmanuel Jammeh, Lingfen Sun, Asiya Khan, & Emmanuel Ifeachor. (2009). Open IMS Core with VoIP Quality Adaptation. 295–300. 7 indexed citations
17.
Khan, Asiya, Lingfen Sun, & Emmanuel Ifeachor. (2009). Content Clustering Based Video Quality Prediction Model for MPEG4 Video Streaming over Wireless Networks. Zenodo (CERN European Organization for Nuclear Research). 5. 1–5. 72 indexed citations
18.
Khan, Asiya, Lingfen Sun, & Emmanuel Ifeachor. (2008). An ANFIS-Based Hybrid Video Quality Prediction Model for Video Streaming over Wireless Networks. 357–362. 16 indexed citations
19.
Sun, Lingfen, et al.. (2006). Adaptive Multi-Copy Routing for Intermittently Connected Mobile Ad Hoc Networks. Global Communications Conference. 13 indexed citations
20.
Sun, Lingfen & Emmanuel Ifeachor. (2004). Prediction of perceived conversational speech quality and effects of playout buffer algorithms. 1. 1–6. 24 indexed citations

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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