Aristidis Likas

147 papers receiving 6.8k citations

Hit Papers

The global k-means clustering algorithm20022026201020182002200850010001.5k2.0k

Peers

Aristidis Likas
Comparison fields: 5 of 207
  • Artificial Intelligence 2.8k
  • Computer Vision and Pattern Recognition 2.1k
  • Signal Processing 799
  • Statistical and Nonlinear Physics 555
  • Electrical and Electronic Engineering 545
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Mark E. Shields United States
Onur Teymur United Kingdom
Michel Verleysen Belgium
Olivier Bousquet France
Joachim M. Buhmann Switzerland
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Countries citing papers authored by Aristidis Likas

Since Specialization
Citations

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

Fields of papers citing papers by Aristidis Likas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aristidis Likas

This figure shows the co-authorship network connecting the top 25 collaborators of Aristidis Likas. A scholar is included among the top collaborators of Aristidis Likas 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 Aristidis Likas. Aristidis Likas 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 0
2 0
3 2
4 1
5 2
6
Dip-means: an incremental clustering method for estimating the number of clusters
47
7 62
8 5
9
Variational Bayesian blind image deconvolution based on a sparse kernel model for the point spread function
0
10
Neural splines: exploiting parallelism for function approximation using modular neural networks
0
11 69
12
Neural network assisted crack and flow identification in transient dynamics
5
13
Bayesian regression of functional neuroimages
2
14 107
15 74
16 42
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A parallelizable operation scheme of the Boltzmann machine optimizer based on group updates
1
18 3
19
Embedding knowledge into stochastic learning automata for fast solution of binary constraint satisfaction problems.
2
20
Collision-free movement of an autonomous vehicle using reinforcement learning
7

About Aristidis Likas

Aristidis Likas is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 153 papers that have together received 7.1k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (24 papers), Neural Networks and Applications (18 papers) and Face and Expression Recognition (17 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Artificial Intelligence (2.8k citations) and Signal Processing (799 citations). Aristidis Likas has collaborated with scholars based in Greece, United States and Netherlands. Frequent co-authors include Nikos Vlassis, Jakob Verbeek, Nikolaos Galatsanos, Grigorios Tzortzis, Dimitris Tzikas, I.E. Lagaris, Dimitrios I. Fotiadis, D.G. Papageorgiou, Christophoros Nikou and Constantinos Constantinopoulos. Their work appears in journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence and European Journal of Operational Research.

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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