Michael Gygli
- Signal Processing top 2%
- Speech and Audio Processing 2
- Music and Audio Processing 2
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- Advanced Image and Video Retrieval Techniques 7
- Video Analysis and Summarization 6
- Multimodal Machine Learning Applications 4
- Image Retrieval and Classification Techniques 3
- Visual Attention and Saliency Detection 2
- Video Surveillance and Tracking Methods 2
- Developmental Biology top 10%
- Artificial Intelligence top 10%
- Co-authors
- Luc Van GoolHelmut GräbnerNaoya TakahashiLiangliang CaoYale SongHayko RiemenschneiderBeat PfisterFabian Nater
- Journals
- IEEE Transactions on Multimedia (1 paper)Lirias (KU Leuven) (5 papers)MediaEval (1 paper)
- Partner nations
- SwitzerlandBelgiumUnited States
In The Last Decade
Michael Gygli
14 papers receiving 726 citations
Peers
Comparison fields: 5 of 78
- Signal Processing 317
- Computer Vision and Pattern Recognition 601
- Developmental Biology 21
- Human-Computer Interaction 24
- Artificial Intelligence 133
Countries citing papers authored by Michael Gygli
This map shows the geographic impact of Michael Gygli'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 Michael Gygli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Gygli more than expected).
Fields of papers citing papers by Michael Gygli
This network shows the impact of papers produced by Michael Gygli. 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 Michael Gygli. The network helps show where Michael Gygli may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Michael Gygli, 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 | 2024 | 1 | |
| 2 | 2017 | 114 | |
| 3 | 2017 | 34 | |
| 4 | 2017 | 4 | |
| 5 | 2016 | 99 | |
| 6 | ETH-CVL @ MediaEval 2016: Textual-Visual Embeddings and Video2GIF for Video Interestingness. | 2016 | 3 |
| 7 | 2016 | 87 | |
| 8 | 2016 | 14 | |
| 9 | 2016 | 10 | |
| 10 | 2015 | 263 | |
| 11 | ETH-CVL @ MediaEval 2015: Learning Objective Functions for Improved Image Retrieval | 2015 | 1 |
| 12 | 2014 | 7 | |
| 13 | 2013 | 113 | |
| 14 | 2013 | 11 |
About Michael Gygli
Michael Gygli is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Human-Computer Interaction, having authored 14 papers that have together received 761 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (7 papers), Video Analysis and Summarization (6 papers), Multimodal Machine Learning Applications (4 papers), Image Retrieval and Classification Techniques (3 papers), Speech and Audio Processing (2 papers), Visual Attention and Saliency Detection (2 papers), Music and Audio Processing (2 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Signal Processing (317 citations), Computer Vision and Pattern Recognition (601 citations) and Developmental Biology (21 citations). Michael Gygli has collaborated with scholars based in Switzerland, Belgium and United States. Frequent co-authors include Luc Van Gool, Helmut Gräbner, Naoya Takahashi, Liangliang Cao, Yale Song, Hayko Riemenschneider, Beat Pfister, Fabian Nater, Dengxin Dai and Santiago Manén. Their work appears in journals such as IEEE Transactions on Multimedia, Lirias (KU Leuven) and MediaEval.
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.