Markus Svensén

19 papers receiving 2.6k citations

Markus Svensén's Hit Papers

Potential, challenges and future directions for deep learning in prognostics and health management applications 2020 · 395 citations
3950+9+18Years since publication2505007501000

Peers

Markus Svensén
Comparison fields: 5 of 160
  • Signal Processing 458
  • Computer Vision and Pattern Recognition 753
  • Artificial Intelligence 1.1k
  • Computational Mathematics 10
  • Control and Systems Engineering 375
Replace Shirish Shevade with:
Shirish Shevade India
Chiranjib Bhattacharyya India
John S. Denker United States
Belur V. Dasarathy United States
Michèle Basseville France
Glenn Fung United States
Yanhui Guo United States
Sheng‐De Wang Taiwan
Mahesan Niranjan United Kingdom
Masoud Nikravesh United States
Markus Svensén relative to Shirish Shevade India Shirish Shevade's profile →
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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

19 of 19 papers shown
#Work
1
GTM: The Generative Topographic Mapping
Hit paper breakdown →
19981089
2
Potential, challenges and future directions for deep learning in prognostics and health management applications
Hit paper breakdown →
2020395
3 2010326
4 2005194
5
Advances in Neural Information Processing Systems 15 (NIPS 2002)
1996182
6 1998166
7 2002117
8 1996109
9 200455
10 200038
11
Magnification factors for the SOM and GTM algorithms
199726
12
Proceedings 1997 Workshop on Self-Organizing Maps
199722
13 200014
14 201813
15
EM Optimization of Latent-Variable Density Models
199512
16
Proceedings of the Fifth International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD)
20117
17 19996
18 20016
19
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, Radiology, Nuclear Medicine and Imaging, Control and Systems Engineering and Statistical and Nonlinear Physics, having authored 19 papers that have together received 2.8k indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Advanced Neuroimaging Techniques and Applications (3 papers), Blind Source Separation Techniques (2 papers), Neural dynamics and brain function (2 papers), Advanced MRI Techniques and Applications (2 papers), Image Processing and 3D Reconstruction (2 papers), Fault Detection and Control Systems (2 papers) and Ultrasound Imaging and Elastography (1 paper). The work is most often cited by research in Signal Processing (458 citations), Computer Vision and Pattern Recognition (753 citations), Artificial Intelligence (1.1k citations), Computational Mathematics (10 citations) and Control and Systems Engineering (375 citations). Markus Svensén has collaborated with scholars based in United Kingdom, Germany and France. Frequent co-authors include Chris Bishop, Christopher K. I. Williams, Mélanie Ducoffe, Olga Fink, Pierre Dersin, Qin Wang, Wan-Jui Lee, Frithjof Kruggel, Adnan Čustović and David Heckerman. Their work appears in journals such as Neurocomputing, IEEE Transactions on Medical Imaging, Engineering Applications of Artificial Intelligence, American Journal of Respiratory and Critical Care Medicine and NeuroImage.

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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