Łukasz Romaszko
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- Advanced Vision and Imaging 2
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- Neural Networks and Applications 1
- Machine Learning and Algorithms 1
- Semantic Web and Ontologies 1
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- Elasticity and Material Modeling 3
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- Cardiovascular Function and Risk Factors 3
- Cardiac Valve Diseases and Treatments 2
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- EEG and Brain-Computer Interfaces 1
- Co-authors
- Christopher K. I. WilliamsIsabelle GuyonDirk HusmeierSérgio EscaleraHugo Jair EscalanteColin BerryAlexander StatnikovXiaoyu Luo
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceHealth Information Management
- Journals
- Pattern Recognition (1 paper)Artificial Intelligence in Medicine (1 paper)Edinburgh Research Explorer (1 paper)
- Partner nations
- United KingdomMexicoAndorra
In The Last Decade
Łukasz Romaszko
8 papers receiving 62 citations
Peers
Comparison fields: 5 of 36
- Computer Vision and Pattern Recognition 17
- Artificial Intelligence 25
- Health Information Management 3
- Building and Construction 8
- Computer Graphics and Computer-Aided Design 2
Countries citing papers authored by Łukasz Romaszko
This map shows the geographic impact of Łukasz Romaszko'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 Łukasz Romaszko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Łukasz Romaszko more than expected).
Fields of papers citing papers by Łukasz Romaszko
This network shows the impact of papers produced by Łukasz Romaszko. 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 Łukasz Romaszko. The network helps show where Łukasz Romaszko may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Łukasz Romaszko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 13 | |
| 2 | 2020 | 3 | |
| 3 | 2019 | 2 | |
| 4 | 2019 | 2 | |
| 5 | 2017 | 8 | |
| 6 | A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention | 2016 | 28 |
| 7 | Signal Correlation Prediction Using Convolutional Neural Networks | 2015 | 3 |
| 8 | 2010 | 5 |
About Łukasz Romaszko
Łukasz Romaszko is a scholar working on Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 8 papers that have together received 64 indexed citations. Recurring topics across this work include Elasticity and Material Modeling (3 papers), Cardiovascular Function and Risk Factors (3 papers), Cardiac Valve Diseases and Treatments (2 papers), Advanced Vision and Imaging (2 papers), Neural Networks and Applications (1 paper), EEG and Brain-Computer Interfaces (1 paper), Machine Learning and Algorithms (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (17 citations), Artificial Intelligence (25 citations) and Health Information Management (3 citations). Łukasz Romaszko has collaborated with scholars based in United Kingdom, Mexico and Andorra. Frequent co-authors include Christopher K. I. Williams, Isabelle Guyon, Dirk Husmeier, Sérgio Escalera, Hugo Jair Escalante, Colin Berry, Alexander Statnikov, Xiaoyu Luo, David R. Dalton and James Robert Lloyd. Their work appears in journals such as Pattern Recognition, Artificial Intelligence in Medicine and Edinburgh Research Explorer.
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.