Alfred Ultsch

5.5k citations
135 papers · 3.0k indexed · h-index 30
Topics
Neural Networks and Applications (19 papers)Gene expression and cancer classification (16 papers)Olfactory and Sensory Function Studies (14 papers)
Journals
SHILAP Revista de lepidopterologíaBloodBioinformatics

In The Last Decade

Alfred Ultsch

131 papers receiving 2.8k citations

Peers

Alfred Ultsch
Comparison fields: 5 of 192
  • Artificial Intelligence 788
  • Molecular Biology 508
  • Signal Processing 421
  • Computer Vision and Pattern Recognition 375
  • Physiology 354
Replace Chih‐Wei Hsu with:
Chih‐Wei Hsu Taiwan
Kun Huang United States
Sultan Ahmad Saudi Arabia
Martti Juhola Finland
Massimo Buscema Italy
Vladimir Svetnik United States
Xi Zhang China
Zhi Liu China
Lars Karlsson Sweden
Francisco Azuaje United Kingdom
Alfred Ultsch relative to Chih‐Wei Hsu Taiwan Chih‐Wei Hsu's profile →
Citations per field
00.5×1.5×1.9×
Chih‐Wei Hsu · 1×
Citations per year

Countries citing papers authored by Alfred Ultsch

Since Specialization
Citations

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

Fields of papers citing papers by Alfred Ultsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alfred Ultsch

This figure shows the co-authorship network connecting the top 25 collaborators of Alfred Ultsch. A scholar is included among the top collaborators of Alfred Ultsch 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 Alfred Ultsch. Alfred Ultsch 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 1
2 1
3 4
4 7
5 2
6 4
7 14
8 47
9 14
10 8
11 4
12 55
13
Is Log Ratio a Good Value for Measuring Return in Stock Investments
1
14 5
15
An algorithm for fast and reliable ESOM learning
8
16
U*F Clustering: A New Performant “Cluster-Mining” Method Based On Segmentation of Self-Organizing Maps
2
17
U*C: Self-organized Clustering with Emergent Feature Maps.
7
18 122
19 23
20
Neural Networks and Their Rules for Classification in Marine Geology
1

About Alfred Ultsch

Alfred Ultsch is a scholar working on Sensory Systems, Signal Processing and Artificial Intelligence, having authored 135 papers that have together received 3.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (19 papers), Gene expression and cancer classification (16 papers) and Olfactory and Sensory Function Studies (14 papers). The work is most often cited by research in Sensory Systems (301 citations), Health Informatics (75 citations) and Signal Processing (421 citations). Alfred Ultsch has collaborated with scholars based in Germany, Finland and United States. Frequent co-authors include Jörn Lötsch, Michael C. Thrun, Fabian Mörchen, Dario Kringel, Thomas Hummel, Gerd Geißlinger, B. Oertel, Eija Kalso, Alexandra Doehring and F. Javier Lerch. Their work appears in journals such as SHILAP Revista de lepidopterología, Blood and Bioinformatics.

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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