Thomas Lidy
- Signal Processing top 2%
- Music and Audio Processing 20
- Speech and Audio Processing 15
- Time Series Analysis and Forecasting 2
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- Music Technology and Sound Studies 18
- Generative Adversarial Networks and Image Synthesis 2
- Augmented Reality Applications 1
- Music top 5%
- Human-Computer Interaction top 10%
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- Neural Networks and Applications 3
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- Marine animal studies overview 1
- Co-authors
- Andreas RauberXavier SerraJordi PonsJosé M. IñestaAntonio PertusaHannes KaufmannDieter SchmalstiegGerhard Reitmayr
- Journals
- Signal Processing (1 paper)Multimedia Tools and Applications (1 paper)DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (1 paper)
In The Last Decade
Thomas Lidy
24 papers receiving 466 citations
Peers
Comparison fields: 5 of 71
- Signal Processing 376
- Computer Vision and Pattern Recognition 373
- Music 39
- Human-Computer Interaction 33
- Developmental Biology 12
Countries citing papers authored by Thomas Lidy
This map shows the geographic impact of Thomas Lidy'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 Thomas Lidy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Lidy more than expected).
Fields of papers citing papers by Thomas Lidy
This network shows the impact of papers produced by Thomas Lidy. 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 Thomas Lidy. The network helps show where Thomas Lidy may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Thomas Lidy, 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 | 2018 | 7 | |
| 2 | A Multi-modal Deep Neural Network approach to Bird-song identification. | 2017 | 4 |
| 3 | 2016 | 72 | |
| 4 | Comparing Shallow versus Deep Neural Network Architectures for Automatic Music Genre Classification. | 2016 | 23 |
| 5 | 2010 | 9 | |
| 6 | 2009 | 35 | |
| 7 | 2009 | 4 | |
| 8 | 2008 | 11 | |
| 9 | Automatic Audio Segmentation: Segment Boundary and Structure Detection in Popular Music | 2008 | 25 |
| 10 | Audio music classification using a combination of spectral, timbral, rhythmic, temporal and symbolic features | 2008 | 1 |
| 11 | 2008 | 7 | |
| 12 | 2008 | 4 | |
| 13 | 2007 | 3 | |
| 14 | 2007 | 54 | |
| 15 | The Map of Mozart. | 2006 | 12 |
| 16 | 2006 | 3 | |
| 17 | 2006 | 3 | |
| 18 | SOUND RE-SYNTHESIS FROM RHYTHM PATTERN FEATURES - AUDIBLE INSIGHT INTO A MUSIC FEATURE EXTRACTION PROCESS | 2005 | 6 |
| 19 | 2005 | 143 | |
| 20 | 2003 | 71 |
About Thomas Lidy
Thomas Lidy is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Developmental Biology, Music and Museology, having authored 24 papers that have together received 509 indexed citations. Recurring topics across this work include Music and Audio Processing (20 papers), Music Technology and Sound Studies (18 papers), Speech and Audio Processing (15 papers), Neural Networks and Applications (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Time Series Analysis and Forecasting (2 papers), Marine animal studies overview (1 paper) and Augmented Reality Applications (1 paper). The work is most often cited by research in Signal Processing (376 citations), Computer Vision and Pattern Recognition (373 citations), Music (39 citations), Human-Computer Interaction (33 citations) and Developmental Biology (12 citations). Thomas Lidy has collaborated with scholars based in Austria, Spain and Malaysia. Frequent co-authors include Andreas Rauber, Xavier Serra, Jordi Pons, José M. Iñesta, Antonio Pertusa, Hannes Kaufmann, Dieter Schmalstieg, Gerhard Reitmayr, Alexander Schindler and Rudolf Mayer. Their work appears in journals such as Signal Processing, Multimedia Tools and Applications, DROPS (Schloss Dagstuhl – Leibniz Center for Informatics), Zenodo (CERN European Organization for Nuclear Research) and IEEE Transactions on Neural Networks.
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.