Michele Covell
- Computer Vision and Pattern Recognition top 1%
- Signal Processing top 1%
- Artificial Intelligence top 10%
- Control and Systems Engineering top 5%
- Computer Networks and Communications
- Co-authors
- Malcolm SlaneyChristoph BreglerShumeet BalujaSung Jin HwangDamien VincentTroy ChinenJoel ShorGeorge Toderici
- Topics
- Advanced Image and Video Retrieval Techniques (13 papers)Music and Audio Processing (11 papers)Speech and Audio Processing (10 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided Design
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Michele Covell
48 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 1.1k
- Signal Processing 639
- Artificial Intelligence 195
- Control and Systems Engineering 189
- Computer Networks and Communications 57
Countries citing papers authored by Michele Covell
This map shows the geographic impact of Michele Covell'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 Michele Covell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Covell more than expected).
Fields of papers citing papers by Michele Covell
This network shows the impact of papers produced by Michele Covell. 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 Michele Covell. The network helps show where Michele Covell may publish in the future.
Co-authorship network of co-authors of Michele Covell
This figure shows the co-authorship network connecting the top 25 collaborators of Michele Covell. A scholar is included among the top collaborators of Michele Covell based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michele Covell. Michele Covell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 38 | |
| 7 | 68 | |
| 8 | Learning forgiving hash functions: algorithms and large scale tests | 7 |
| 9 | 40 | |
| 10 | 2 | |
| 11 | 28 | |
| 12 | 17 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 8 | |
| 17 | 17 | |
| 18 | FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks | 100 |
| 19 | Video rewrite: visual speech synthesis from video. | 11 |
| 20 | Computer-aided algorithm design and rearrangement | 2 |
About Michele Covell
Michele Covell is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Transportation, having authored 49 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (13 papers), Music and Audio Processing (11 papers) and Speech and Audio Processing (10 papers). The work is most often cited by research in Signal Processing (639 citations), Computer Vision and Pattern Recognition (1.1k citations) and Computer Graphics and Computer-Aided Design (36 citations). Michele Covell has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Malcolm Slaney, Christoph Bregler, Shumeet Baluja, Sung Jin Hwang, Damien Vincent, Troy Chinen, Joel Shor, George Toderici, David Minnen and Nick Johnston. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Computer.
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.