Niklas Lavesson
Impact in
- Signal Processing top 5%
- Advanced Malware Detection Techniques
- Artificial Intelligence top 5%
- Data Stream Mining Techniques
- Machine Learning and Data Classification
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Data Mining and Machine Learning Applications 7
- Spam and Phishing Detection 7
- Software Engineering Research 5
- Data Mining Algorithms and Applications 5
-
- Machine Learning and Data Classification 8
- Text and Document Classification Technologies 5
- Co-authors
- Paul Davidsson (14 shared papers)Håkan Grahn (17 shared papers)Henric Johnson (8 shared papers)Eva García-Martín (9 shared papers)Veselka Boeva (14 shared papers)Hüseyin Kusetoğulları (2 shared papers)Martin Boldt (6 shared papers)Amir Yavariabdi (1 shared paper)
In The Last Decade
Niklas Lavesson
76 papers receiving 882 citations
Peers
Comparison fields: 5 of 94
- Signal Processing 117
- Artificial Intelligence 271
- Computer Vision and Pattern Recognition 146
- Information Systems 142
- Hardware and Architecture 34
Countries citing papers authored by Niklas Lavesson
This map shows the geographic impact of Niklas Lavesson'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 Niklas Lavesson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niklas Lavesson more than expected).
Fields of papers citing papers by Niklas Lavesson
This network shows the impact of papers produced by Niklas Lavesson. 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 Niklas Lavesson. The network helps show where Niklas Lavesson may publish in the future.
Co-authors
The 25 scholars most cited alongside Niklas Lavesson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 63 | |
| 2 | 2020 | 58 | |
| 3 | 2013 | 53 | |
| 4 | Quantifying the impact of learning algorithm parameter tuning | 2006 | 46 |
| 5 | 2011 | 41 | |
| 6 | 2018 | 39 | |
| 7 | 2011 | 34 | |
| 8 | 2010 | 33 | |
| 9 | Comparative Analysis of Voting Schemes for Ensemble-based Malware Detection | 2013 | 30 |
| 10 | 2022 | 30 | |
| 11 | 2014 | 28 | |
| 12 | Model Based Decision Support for Value and Sustainability in Product Development | 2015 | 28 |
| 13 | 2010 | 22 | |
| 14 | 2010 | 21 | |
| 15 | 2011 | 21 | |
| 16 | 2017 | 20 | |
| 17 | 2011 | 19 | |
| 18 | 2007 | 18 | |
| 19 | 2019 | 17 | |
| 20 | 2014 | 16 |
About Niklas Lavesson
Niklas Lavesson is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 79 papers that have together received 944 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (10 papers), Machine Learning and Data Classification (8 papers), Data Mining and Machine Learning Applications (7 papers), Spam and Phishing Detection (7 papers), Handwritten Text Recognition Techniques (6 papers), Software Engineering Research (5 papers), Text and Document Classification Technologies (5 papers) and Data Mining Algorithms and Applications (5 papers). The work is most often cited by research in Signal Processing (117 citations), Artificial Intelligence (271 citations), Computer Vision and Pattern Recognition (146 citations), Information Systems (142 citations) and Hardware and Architecture (34 citations). Niklas Lavesson has collaborated with scholars based in Sweden, Bulgaria and Germany. Frequent co-authors include Paul Davidsson, Håkan Grahn, Henric Johnson, Eva García-Martín, Veselka Boeva, Hüseyin Kusetoğulları, Martin Boldt, Amir Yavariabdi, Johan Hall and Dirk Vanhoudt. Their work appears in journals such as Expert Systems with Applications, Knowledge and Information Systems, Empirical Software Engineering, Sensors and Journal of Systems and Software.
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.