Markus Svensén

3.5k citations
16 papers · 2.1k · 2 hit papers · h-index 12

Impact in

Papers in

Markus Svensén

16 papers receiving 2.0k citations

Markus Svensén's Hit Papers

Potential, challenges and future directions for deep learning in prognostics and health management applications 2020 · 357 citations
3570+9+18Years since publication250500750

Peers

Markus Svensén
Comparison fields: 5 of 158
  • Signal Processing 297
  • Computer Vision and Pattern Recognition 527
  • Artificial Intelligence 756
  • Immunology and Allergy 113
  • Control and Systems Engineering 327
Replace C.M. Bishop with:
C.M. Bishop United Kingdom
Steven K. Rogers United States
Yanhui Guo United States
Mahesan Niranjan United Kingdom
J Figueroa Nazuno Mexico
Sabri Boughorbel Qatar
P. A. Estévez Chile
Nicolas Vayatis France
Robert Nowak Poland
Masoud Nikravesh United States
Markus Svensén relative to C.M. Bishop United Kingdom C.M. Bishop's profile →
Citations per field
00.5×6.8×
C.M. Bishop · 1×
Citations per year

Countries citing papers authored by Markus Svensén

Since Specialization
Citations

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

Fields of papers citing papers by Markus Svensén

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Markus Svensén, 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 Markus Svensén Line = papers co-authored together Markus Svensén links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
GTM: The Generative Topographic Mapping
Hit paper breakdown →
1998875
2
Potential, challenges and future directions for deep learning in prognostics and health management applications
Hit paper breakdown →
2020357
3 2010311
4 2005183
5 1998139
6 2002110
7 200446
8 200037
9
Magnification factors for the SOM and GTM algorithms
199718
10
Proceedings 1997 Workshop on Self-Organizing Maps
199717
11 201813
12 200012
13
EM Optimization of Latent-Variable Density Models
199511
14
Proceedings of the Fifth International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD)
20116
15 20015
16
Broad vs Narrow: Modelling Strategies for Online Behavioural Targeting
20111

About Markus Svensén

Markus Svensén is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Statistical and Nonlinear Physics and Cognitive Neuroscience, having authored 16 papers that have together received 2.1k indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Image Processing and 3D Reconstruction (2 papers), Fault Detection and Control Systems (2 papers), Blind Source Separation Techniques (2 papers), Neural dynamics and brain function (2 papers), Allergic Rhinitis and Sensitization (1 paper) and Face and Expression Recognition (1 paper). The work is most often cited by research in Signal Processing (297 citations), Computer Vision and Pattern Recognition (527 citations), Artificial Intelligence (756 citations), Immunology and Allergy (113 citations) and Control and Systems Engineering (327 citations). Markus Svensén has collaborated with scholars based in United Kingdom, Germany and France. Frequent co-authors include Chris Bishop, Christopher K. I. Williams, Olga Fink, Qin Wang, Pierre Dersin, Mélanie Ducoffe, Wan-Jui Lee, Frithjof Kruggel, Vincent Y. F. Tan and Angela Simpson. Their work appears in journals such as Neurocomputing, IEEE Transactions on Medical Imaging, Neural Computation, NeuroImage and Engineering Applications of Artificial Intelligence.

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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