Ethem Alpaydın

77 papers receiving 3.0k citations

Hit Papers

Multiple Kernel Learning Algorithms2011202620162021201120212505007501000

Peers

Ethem Alpaydın
Comparison fields: 5 of 172
  • Artificial Intelligence 1.6k
  • Computer Vision and Pattern Recognition 1.3k
  • Signal Processing 293
  • Molecular Biology 291
  • Media Technology 263
Replace Zhihui Li with:
Zhihui Li China
S. Lecœuche France
豊 松尾
Patrice Simard United States
Tobias Scheffer Germany
Barbara Hammer Germany
Wenzhong Guo China
John S. Denker United States
Alan Wee‐Chung Liew Australia
Andrew B. Goldberg United States
Ethem Alpaydın relative to Zhihui Li China Zhihui Li's profile →
Citations per field
00.5×10×14.4×
Zhihui Li · 1×
Citations per year

Countries citing papers authored by Ethem Alpaydın

Since Specialization
Citations

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

Fields of papers citing papers by Ethem Alpaydın

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ethem Alpaydın

This figure shows the co-authorship network connecting the top 25 collaborators of Ethem Alpaydın. A scholar is included among the top collaborators of Ethem Alpaydın 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 Ethem Alpaydın. Ethem Alpaydın 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 2
2
Machine Learningbreakdown →
183
3
Soft decision trees
12
4 14
5 2
6
Multiple Kernel Learning Algorithmsbreakdown →
1156
7 24
8 53
9 1
10
Handling of Deterministic Relationships in Constraint-based Causal Discovery.
3
11 18
12 62
13 72
14
Combining Multiple Representations for Pen-based Handwritten Digit Recognition
38
15 66
16
MultiStage Cascading of Multiple Classifiers: One Man's Noise is Another Man's Data
27
17 18
18 54
19
Selective Attention for Handwritten Digit Recognition
7
20
Optical character recognition using artificial neural networks
4

About Ethem Alpaydın

Ethem Alpaydın is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 80 papers that have together received 3.1k indexed citations. Recurring topics across this work include Face and Expression Recognition (31 papers), Neural Networks and Applications (28 papers) and Machine Learning and Data Classification (13 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Artificial Intelligence (1.6k citations) and Media Technology (263 citations). Ethem Alpaydın has collaborated with scholars based in Türkiye, United States and Netherlands. Frequent co-authors include Mehmet Gönen, Olcay Taner Yıldız, Lale Akarun, Andrea Baraldi, Albert Ali Salah, Ozan İrsoy, Aydın Ulaş, Michael I. Jordan, Eddy Mayoraz and Berk Gökberk. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, European Journal of Operational Research and Pattern Recognition.

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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