D. Mlynek

39 papers receiving 403 citations

Peers

D. Mlynek
Comparison fields: 5 of 47
  • Signal Processing 234
  • Computer Vision and Pattern Recognition 208
  • Music 22
  • Hardware and Architecture 35
  • Artificial Intelligence 130
Replace Camilo Rueda with:
Camilo Rueda Colombia
Tim Crawford United Kingdom
Saikat Dutta India
Alex Strong Germany
Asoke Kumar Datta United States
Dmitri Asonov United States
Yi Ren China
Murilo B. de Carvalho Brazil
Chris Bartels United States
Nikko Ström United States
D. Mlynek relative to Camilo Rueda Colombia Camilo Rueda's profile →
Citations per field
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Citations per year

Countries citing papers authored by D. Mlynek

Since Specialization
Citations

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

Fields of papers citing papers by D. Mlynek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside D. Mlynek, 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 D. Mlynek Line = papers co-authored together D. Mlynek links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006211
2 199451
3 200016
4 200313
5
A New Architecture for an Automatic Generation of Fast Pipelined Adders
199112
6 199912
7 200211
8 200211
9 199210
10 200210
11 20047
12 20016
13
A MIXTURE OF SUPPORT VECTOR MACHINES FOR AUDIO CLASSIFICATION
20055
14 20025
15
Hardware evaluation of EPFL proposal for MPEG-II
19915
16 20055
17 20034
18 19994
19
A Method to Implement a Knowledge-Based system for Fast Prototyping of Hardware Designs
19964
20 20023

About D. Mlynek

D. Mlynek is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Electrical and Electronic Engineering, Artificial Intelligence and Hardware and Architecture, having authored 49 papers that have together received 440 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (13 papers), Advanced Data Compression Techniques (13 papers), Embedded Systems Design Techniques (8 papers), Digital Filter Design and Implementation (7 papers), Parallel Computing and Optimization Techniques (7 papers), Neural Networks and Applications (7 papers), Analog and Mixed-Signal Circuit Design (6 papers) and Model-Driven Software Engineering Techniques (4 papers). The work is most often cited by research in Signal Processing (234 citations), Computer Vision and Pattern Recognition (208 citations), Music (22 citations), Hardware and Architecture (35 citations) and Artificial Intelligence (130 citations). D. Mlynek has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Giorgio Zoia, M.J. Patyra, L. Lemaître, Yusuf Leblebici, Marco Mattavelli, Alexandre Schmid, Abraham Kandel, Horia-Nicolai Teodorescu, H.‐J. Zimmermann and Frank K. Gürkaynak. Their work appears in journals such as IEEE Transactions on Consumer Electronics, Proceedings of the IEEE, Electronics Letters, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Signal Processing Magazine.

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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