M. Kalman

607 citations
16 papers · 429 · h-index 11

Impact in

Papers in

M. Kalman

16 papers receiving 387 citations

Peers

M. Kalman
Comparison fields: 5 of 31
  • Signal Processing 227
  • Computer Vision and Pattern Recognition 266
  • Computer Networks and Communications 222
  • Computer Graphics and Computer-Aided Design 13
  • Electrical and Electronic Engineering 190
Replace Aditya Mavlankar with:
Aditya Mavlankar United States
Rafael Huysegems Belgium
Yago Sánchez Germany
Hung-Ju Lee United States
Kevin Spiteri United States
Yung-Lyul Lee South Korea
Fan Zhai United States
Y. Eisenberg United States
W. Kwok United States
Zhourong Miao United States
M. Kalman relative to Aditya Mavlankar United States Aditya Mavlankar's profile →
Citations per field
00.5×4.0×
Aditya Mavlankar · 1×
Citations per year

Countries citing papers authored by M. Kalman

Since Specialization
Citations

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

Fields of papers citing papers by M. Kalman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside M. Kalman, 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 M. Kalman Line = papers co-authored together M. Kalman links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2004153
2 200352
3 200533
4 200430
5 200727
6 200327
7 200519
8 200517
9 200316
10 200316
11 200414
12 200210
13 20216
14 20054
15 20053
16 20052

About M. Kalman

M. Kalman is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications, Electrical and Electronic Engineering and Sociology and Political Science, having authored 16 papers that have together received 429 indexed citations. Recurring topics across this work include Image and Video Quality Assessment (10 papers), Video Coding and Compression Technologies (10 papers), Advanced Wireless Network Optimization (6 papers), Network Traffic and Congestion Control (4 papers), Advanced Vision and Imaging (3 papers), Cooperative Communication and Network Coding (2 papers), Peer-to-Peer Network Technologies (2 papers) and Multimedia Communication and Technology (2 papers). The work is most often cited by research in Signal Processing (227 citations), Computer Vision and Pattern Recognition (266 citations), Computer Networks and Communications (222 citations), Computer Graphics and Computer-Aided Design (13 citations) and Electrical and Electronic Engineering (190 citations). M. Kalman has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Bernd Girod, Eckehard Steinbach, P. Ramanathan, Rui Zhang, Peter van Beek, Isaac Keslassy, Behrouz H. Far, Eric Setton, J Apostolopoulos and Athina Markopoulou. Their work appears in journals such as IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, Proceedings - International Conference on Image Processing and 2021 International Conference on Computational Science and Computational Intelligence (CSCI).

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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