Jason Lines
Impact in
- Signal Processing top 0.2%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications
- Advanced Text Analysis Techniques
- Neural Networks and Applications
Papers in ⓘ
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- Time Series Analysis and Forecasting 10
- Music and Audio Processing 6
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- Complex Systems and Time Series Analysis 6
- Co-authors
- Anthony Bagnall (12 shared papers)Aaron Bostrom (3 shared papers)Jon Hills (5 shared papers)James Large (2 shared papers)Eamonn Keogh (1 shared paper)Sarah Taylor (2 shared papers)Luke M. Davis (3 shared papers)James Mapp (1 shared paper)
- Journals
- Data Mining and Knowledge Discovery (4 papers)Frontiers in Earth Science (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)International Journal of Neural Systems (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Jason Lines
15 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Signal Processing 2.0k
- Artificial Intelligence 1.6k
- Economics and Econometrics 487
- Management Science and Operations Research 134
- Computer Vision and Pattern Recognition 201
Countries citing papers authored by Jason Lines
This map shows the geographic impact of Jason Lines'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 Jason Lines with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Lines more than expected).
Fields of papers citing papers by Jason Lines
This network shows the impact of papers produced by Jason Lines. 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 Jason Lines. The network helps show where Jason Lines may publish in the future.
Co-authors
The 13 scholars most cited alongside Jason Lines, 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 | The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances Hit paper breakdown → | 2016 | 801 |
| 2 | Time series classification with ensembles of elastic distance measures Hit paper breakdown → | 2014 | 333 |
| 3 | Classification of time series by shapelet transformation Hit paper breakdown → | 2013 | 330 |
| 4 | Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles Hit paper breakdown → | 2015 | 277 |
| 5 | 2012 | 237 | |
| 6 | 2018 | 206 | |
| 7 | 2016 | 103 | |
| 8 | 2012 | 65 | |
| 9 | 2019 | 54 | |
| 10 | 2016 | 46 | |
| 11 | 2014 | 17 | |
| 12 | 2012 | 13 | |
| 13 | 2019 | 4 | |
| 14 | Detecting right whales from autonomous surface vehicles using RNNs and CNNs | 2019 | 3 |
| 15 | 2024 | 2 |
About Jason Lines
Jason Lines is a scholar working on Signal Processing, Economics and Econometrics, Artificial Intelligence, Oceanography and Ecology, having authored 15 papers that have together received 2.5k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (10 papers), Complex Systems and Time Series Analysis (6 papers), Music and Audio Processing (6 papers), Anomaly Detection Techniques and Applications (5 papers), Marine animal studies overview (2 papers), Underwater Acoustics Research (2 papers), Advanced Chemical Sensor Technologies (1 paper) and Dental Radiography and Imaging (1 paper). The work is most often cited by research in Signal Processing (2.0k citations), Artificial Intelligence (1.6k citations), Economics and Econometrics (487 citations), Management Science and Operations Research (134 citations) and Computer Vision and Pattern Recognition (201 citations). Jason Lines has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Anthony Bagnall, Aaron Bostrom, Jon Hills, James Large, Eamonn Keogh, Sarah Taylor, Luke M. Davis, James Mapp, Andoni P. Toms and Barry-John Theobald. Their work appears in journals such as Data Mining and Knowledge Discovery, Frontiers in Earth Science, ACM Transactions on Knowledge Discovery from Data, International Journal of Neural Systems and IEEE Transactions on Knowledge and Data Engineering.
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.