Michael Seufert

123 papers receiving 2.4k citations

Hit Papers

A Survey on Quality of Experience of HTTP Adaptive Streaming20142026201820222014200400600

Peers

Michael Seufert
Comparison fields: 5 of 96
  • Computer Vision and Pattern Recognition 1.8k
  • Computer Networks and Communications 1.1k
  • Signal Processing 741
  • Sociology and Political Science 538
  • Electrical and Electronic Engineering 388
Replace Sebastian Egger with:
Sebastian Egger Austria
Thomas Zinner Germany
Pedro Casas Austria
Jibin Zhan United States
Jeffrey Pang United States
Kun Gai China
Anirban Mahanti Canada
Xavier Amatriain Spain
Dilip Joseph United States
Martı́n Varela Finland
Michael Seufert relative to Sebastian Egger Austria Sebastian Egger's profile →
Citations per field
00.5×1.5×2.3×
Sebastian Egger · 1×
Citations per year

Countries citing papers authored by Michael Seufert

Since Specialization
Citations

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

Fields of papers citing papers by Michael Seufert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Seufert

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Seufert. A scholar is included among the top collaborators of Michael Seufert 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 Michael Seufert. Michael Seufert 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
#WorkIndexed citations
1 0
2 0
3 1
4 5
5 8
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11 25
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13
Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks
2
14
ML-Assisted Latency Assignments in Time-Sensitive Networking
2
15 5
16
A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming
3
17 10
18
Quality of experience in remote virtual desktop services
24
19
Socially-Aware Traffic Management.
1
20
Resilience in Enterprise Social Networks.
1

About Michael Seufert

Michael Seufert is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 129 papers that have together received 2.4k indexed citations. Recurring topics across this work include Image and Video Quality Assessment (75 papers), Network Traffic and Congestion Control (33 papers) and Multimedia Communication and Technology (26 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.8k citations), Signal Processing (741 citations) and Computer Networks and Communications (1.1k citations). Michael Seufert has collaborated with scholars based in Germany, Austria and Czechia. Frequent co-authors include Phuoc Tran‐Gia, Tobias Hoßfeld, Thomas Zinner, Raimund Schatz, Pedro Casas, Sebastian Egger, Martin Slanina, Florian Wamser, Matthias Hirth and Christian Sieber. Their work appears in journals such as Soil Biology and Biochemistry, Computers in Human Behavior and IEEE Communications Surveys & Tutorials.

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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