E. Shlomot
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Computational Mechanics top 10%
- Electrical and Electronic Engineering
- Co-authors
- A. BenyassineHuan-yu SuD. MassalouxClaude LamblinJean‐Pierre PetitY.Y. ZeeviV. CupermanA. Gersho
- Topics
- Advanced Data Compression Techniques (14 papers)Speech and Audio Processing (11 papers)Image and Signal Denoising Methods (5 papers)
- Journals
- IEEE Transactions on Signal ProcessingIEEE Communications MagazineIEEE Transactions on Speech and Audio Processing
- Partner nations
- United StatesIsraelGermany
In The Last Decade
E. Shlomot
17 papers receiving 380 citations
Peers
Comparison fields: 5 of 50
- Signal Processing 319
- Computer Vision and Pattern Recognition 185
- Artificial Intelligence 157
- Computational Mechanics 144
- Electrical and Electronic Engineering 38
Countries citing papers authored by E. Shlomot
This map shows the geographic impact of E. Shlomot'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 E. Shlomot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. Shlomot more than expected).
Fields of papers citing papers by E. Shlomot
This network shows the impact of papers produced by E. Shlomot. 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 E. Shlomot. The network helps show where E. Shlomot may publish in the future.
Co-authorship network of co-authors of E. Shlomot
This figure shows the co-authorship network connecting the top 25 collaborators of E. Shlomot. A scholar is included among the top collaborators of E. Shlomot 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 E. Shlomot. E. Shlomot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 44 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 28 | |
| 6 | 8 | |
| 7 | 8 | |
| 8 | 2 | |
| 9 | 12 | |
| 10 | 11 | |
| 11 | 8 | |
| 12 | 7 | |
| 13 | 8 | |
| 14 | Hybrid coding of speech at low bit-rate | 1 |
| 15 | 230 | |
| 16 | 38 | |
| 17 | 8 | |
| 18 | 8 |
About E. Shlomot
E. Shlomot is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 18 papers that have together received 423 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (14 papers), Speech and Audio Processing (11 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Signal Processing (319 citations), Computer Vision and Pattern Recognition (185 citations) and Computational Mechanics (144 citations). E. Shlomot has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include A. Benyassine, Huan-yu Su, D. Massaloux, Claude Lamblin, Jean‐Pierre Petit, Y.Y. Zeevi, V. Cuperman, A. Gersho, William A. Pearlman and N. Peterfreund. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Communications Magazine and IEEE Transactions on Speech and Audio Processing.
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.