Rafal A. Angryk

133 papers receiving 1.0k citations

Peers

Rafal A. Angryk
Comparison fields: 5 of 95
  • Artificial Intelligence 474
  • Signal Processing 340
  • Astronomy and Astrophysics 309
  • Computer Vision and Pattern Recognition 266
  • Information Systems 220
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Countries citing papers authored by Rafal A. Angryk

Since Specialization
Citations

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

Fields of papers citing papers by Rafal A. Angryk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rafal A. Angryk. 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 Rafal A. Angryk. The network helps show where Rafal A. Angryk may publish in the future.

Co-authorship network of co-authors of Rafal A. Angryk

This figure shows the co-authorship network connecting the top 25 collaborators of Rafal A. Angryk. A scholar is included among the top collaborators of Rafal A. Angryk 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 Rafal A. Angryk. Rafal A. Angryk 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 5
4 95
5 9
6
Evaluating Preprocessing Strategies for Time Series Prediction using Deep Learning Architectures.
13
7
A Region-Based Retrieval System for Heliophysics Imagery.
1
8
Spatiotemporal Frequent Pattern Discovery from Solar Event Metadata
1
9
Mitigating the Curse of Dimensionality for Exact kNN Retrieval
8
10
ERMO-DG: Evolving Region Moving Object Dataset Generator
7
11
Mining of Solar Big Data: Challenges and Opportunities
1
12
Cluster Analysis for Optimal Indexing
1
13
Introducing the first publicly available Content-Based Image-Retrieval system for the Solar Dynamics Observatory mission
4
14
Evolving Kernel Functions with Particle Swarms and Genetic Programming
7
15
Automated Weather Sensor Quality Control.
7
16
An Experimental Evaluation of Popular Image Parameters for Monochromatic Solar Image Categorization
22
17
Attribute-oriented defuzzification of fuzzy database tuples with categorical entries
1
18 0
19
Travel Support System - an Agent-Biased Framework.
12
20 10

About Rafal A. Angryk

Rafal A. Angryk is a scholar working on Signal Processing, Computational Mathematics and Astronomy and Astrophysics, having authored 142 papers that have together received 1.1k indexed citations. Recurring topics across this work include Data Management and Algorithms (44 papers), Solar and Space Plasma Dynamics (42 papers) and Data Mining Algorithms and Applications (29 papers). The work is most often cited by research in Signal Processing (340 citations), Astronomy and Astrophysics (309 citations) and Artificial Intelligence (474 citations). Rafal A. Angryk has collaborated with scholars based in United States, Greece and Poland. Frequent co-authors include Berkay Aydin, Juan M. Banda, P. C. H. Martens, Dustin Kempton, Michael A. Schuh, Soukaïna Filali Boubrahimi, Ruizhe Ma, Shah Muhammad Hamdi, Manolis K. Georgoulis and Azim Ahmadzadeh. Their work appears in journals such as The Astrophysical Journal, IEEE Transactions on Pattern Analysis and Machine Intelligence and The Astrophysical Journal Supplement Series.

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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