Werner Van Leekwijck

1.9k total citations · 1 hit paper
37 papers, 1.2k citations indexed

About

Werner Van Leekwijck is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Werner Van Leekwijck has authored 37 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 17 papers in Computer Networks and Communications and 13 papers in Signal Processing. Recurrent topics in Werner Van Leekwijck's work include Image and Video Quality Assessment (22 papers), Video Coding and Compression Technologies (13 papers) and Caching and Content Delivery (11 papers). Werner Van Leekwijck is often cited by papers focused on Image and Video Quality Assessment (22 papers), Video Coding and Compression Technologies (13 papers) and Caching and Content Delivery (11 papers). Werner Van Leekwijck collaborates with scholars based in Belgium, United States and France. Werner Van Leekwijck's co-authors include Etienne E. Kerre, Steven Latré, Filip De Turck, Jeroen Famaey, Tingyao Wu, Niels Bouten, Danny De Vleeschauwer, Bart De Vleeschauwer, Maxim Claeys and Dohy Hong and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, Fuzzy Sets and Systems and Neural Computation.

In The Last Decade

Werner Van Leekwijck

35 papers receiving 1.2k citations

Hit Papers

Defuzzification: criteria and classification 1999 2026 2008 2017 1999 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Werner Van Leekwijck Belgium 16 529 368 347 246 196 37 1.2k
Ye Chen China 19 234 0.4× 192 0.5× 102 0.3× 392 1.6× 137 0.7× 78 1.1k
Gia Nhu Nguyen Vietnam 20 361 0.7× 585 1.6× 211 0.6× 508 2.1× 263 1.3× 68 1.7k
Shie-Jue Lee Taiwan 21 330 0.6× 206 0.6× 193 0.6× 1.0k 4.1× 196 1.0× 120 1.8k
Patrick P. K. Chan China 21 522 1.0× 269 0.7× 332 1.0× 634 2.6× 173 0.9× 118 1.7k
Rami Al‐Hmouz Saudi Arabia 19 194 0.4× 115 0.3× 114 0.3× 583 2.4× 97 0.5× 70 1.3k
Hillol Kargupta United States 22 163 0.3× 421 1.1× 409 1.2× 1.1k 4.6× 91 0.5× 69 1.7k
S. Geetha India 21 519 1.0× 646 1.8× 583 1.7× 800 3.3× 117 0.6× 151 1.9k
Pei‐Wei Tsai China 25 260 0.5× 434 1.2× 119 0.3× 792 3.2× 399 2.0× 91 2.0k
Jianfeng Xu China 17 367 0.7× 163 0.4× 238 0.7× 360 1.5× 114 0.6× 100 1.1k
Jasni Mohamad Zain Malaysia 23 796 1.5× 330 0.9× 254 0.7× 426 1.7× 125 0.6× 151 1.9k

Countries citing papers authored by Werner Van Leekwijck

Since Specialization
Citations

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

Fields of papers citing papers by Werner Van Leekwijck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Werner Van Leekwijck. 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 Werner Van Leekwijck. The network helps show where Werner Van Leekwijck may publish in the future.

Co-authorship network of co-authors of Werner Van Leekwijck

This figure shows the co-authorship network connecting the top 25 collaborators of Werner Van Leekwijck. A scholar is included among the top collaborators of Werner Van Leekwijck 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 Werner Van Leekwijck. Werner Van Leekwijck 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.
Rachkovskij, Dmitri A., et al.. (2025). Margin-Based Training of HDC Classifiers. Big Data and Cognitive Computing. 9(3). 68–68.
2.
Leekwijck, Werner Van, et al.. (2024). Co-learning synaptic delays, weights and adaptation in spiking neural networks. Frontiers in Neuroscience. 18. 1360300–1360300. 7 indexed citations
3.
Leekwijck, Werner Van, et al.. (2024). An encoding framework for binarized images using hyperdimensional computing. Frontiers in Big Data. 7. 1371518–1371518. 1 indexed citations
4.
Leekwijck, Werner Van, et al.. (2023). Training a Hyperdimensional Computing Classifier Using a Threshold on Its Confidence. Neural Computation. 35(12). 2006–2023. 7 indexed citations
5.
Leekwijck, Werner Van, et al.. (2022). Extended liquid state machines for speech recognition. Frontiers in Neuroscience. 16. 1023470–1023470. 11 indexed citations
6.
Claeys, Maxim, Niels Bouten, Danny De Vleeschauwer, et al.. (2016). Cooperative Announcement-Based Caching for Video-on-Demand Streaming. IEEE Transactions on Network and Service Management. 13(2). 308–321. 10 indexed citations
7.
Claeys, Maxim, Niels Bouten, Danny De Vleeschauwer, et al.. (2015). An announcement-based caching approach for video-on-demand streaming. 8 indexed citations
8.
Munteanu, Adrian, et al.. (2015). Perceptual video quality assessment in HTTP adaptive streaming. 72–73. 7 indexed citations
9.
Bouten, Niels, Maxim Claeys, Steven Latré, et al.. (2014). Deadline-based approach for improving delivery of SVC-based HTTP Adaptive Streaming content. 1–7. 12 indexed citations
10.
Famaey, Jeroen, Steven Latré, Niels Bouten, et al.. (2013). On the merits of SVC-based HTTP Adaptive Streaming. Ghent University Academic Bibliography (Ghent University). 419–426. 57 indexed citations
11.
Claeys, Maxim, Steven Latré, Jeroen Famaey, et al.. (2013). Design of a Q-learning-based client quality selection algorithm for HTTP adaptive video streaming. Ghent University Academic Bibliography (Ghent University). 30–37. 47 indexed citations
12.
Bouten, Niels, Steven Latré, Jeroen Famaey, Filip De Turck, & Werner Van Leekwijck. (2013). Minimizing the impact of delay on live SVC-based HTTP adaptive streaming services. Ghent University Academic Bibliography (Ghent University). 1399–1404. 20 indexed citations
13.
Bouten, Niels, Jeroen Famaey, Steven Latré, et al.. (2012). QoE optimization through in-network quality adaptation for HTTP adaptive streaming. 336–342. 32 indexed citations
14.
Schepper, Koen De, et al.. (2012). Shared Content Addressing Protocol (SCAP): Optimizing multimedia content distribution at the transport layer. 36. 302–310. 7 indexed citations
15.
Vleeschauwer, Bart De, et al.. (2012). SVC-Based HTTP Adaptive Streaming. Bell Labs Technical Journal. 16(4). 25–41. 42 indexed citations
16.
17.
Schierl, Thomas, Cornelius Hellge, Thomas Wiegand, et al.. (2011). iDASH. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 257–264. 71 indexed citations
18.
Sánchez, Yago, Thomas Schierl, Cornelius Hellge, et al.. (2011). Efficient HTTP-based streaming using Scalable Video Coding. Signal Processing Image Communication. 27(4). 329–342. 55 indexed citations
19.
Wu, Tingyao, Michael Timmers, Danny De Vleeschauwer, & Werner Van Leekwijck. (2010). On the Use of Reservoir Computing in Popularity Prediction. 304. 19–24. 36 indexed citations
20.
Latré, Steven, Bart De Vleeschauwer, Filip De Turck, et al.. (2009). Design and Configuration of PCN Based Admission Control in Multimedia Aggregation Networks. Ghent University Academic Bibliography (Ghent University). 19. 1–8. 8 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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