S.W. Beet

640 citations
25 papers · 362 indexed · h-index 9

S.W. Beet

20 papers receiving 338 citations

Peers

S.W. Beet
Comparison fields: 5 of 46
  • Signal Processing 284
  • Computer Vision and Pattern Recognition 176
  • Artificial Intelligence 97
  • Pharmacy 15
  • Experimental and Cognitive Psychology 32
Replace José L. Pérez-Córdoba with:
José L. Pérez-Córdoba Spain
Mohamed Faouzi BenZeghiba France
Nicolas Eveno France
P.-Y. Coulon France
Slobodan T. Jovičić Serbia
Shiva Sundaram United States
W. Verhelst Belgium
Juan M. Martín-Doñas Spain
M. A. Anusuya India
Lorenzo Fissore
S.W. Beet relative to José L. Pérez-Córdoba Spain José L. Pérez-Córdoba's profile →
Citations per field
00.5×
José L. Pérez-Córdoba · 1×
Citations per year

Countries citing papers authored by S.W. Beet

Since Specialization
Citations

This map shows the geographic impact of S.W. Beet'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 S.W. Beet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S.W. Beet more than expected).

Fields of papers citing papers by S.W. Beet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.W. Beet. 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 S.W. Beet. The network helps show where S.W. Beet may publish in the future.

Co-authorship network

The 10 scholars most cited alongside S.W. Beet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S.W. Beet Line = papers co-authored together S.W. Beet links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201229
2 20030
3 20022
4 20024
5 20026
6 19981
7 19971
8 199612
9 19965
10 199675
11 19968
12 199647
13 19963
14
Modelling the Flow Inherent in Speech Representations
19940
15 19941
16 19941
17
Visual representations of speech signals
199355
18
Time and frequency resolution in the reduced auditory representation
19930
19 19931
20 19907

About S.W. Beet

S.W. Beet is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Pharmacy, having authored 25 papers that have together received 362 indexed citations. Recurring topics across this work include Speech and Audio Processing (16 papers), Speech Recognition and Synthesis (7 papers), Face recognition and analysis (7 papers), Indoor and Outdoor Localization Technologies (4 papers), Phonetics and Phonology Research (4 papers), Music and Audio Processing (3 papers), Advanced Adaptive Filtering Techniques (3 papers) and Infant Health and Development (2 papers). The work is most often cited by research in Signal Processing (284 citations), Computer Vision and Pattern Recognition (176 citations) and Artificial Intelligence (97 citations). S.W. Beet has collaborated with scholars based in United Kingdom, Switzerland and Australia. Frequent co-authors include Juergen Luettin, N. A. Thacker, Martin Cooke, Neil A. Thacker, Sandra P. Whiteside, C.C. Goodyear, M. Tomlinson, Roger K. Moore, H.E.G. Powrie and M. O. Tokhi. Their work appears in journals such as Computer Speech & Language, IEEE Transactions on Speech and Audio Processing, Electronics Letters, White Rose Research Online (University of Leeds, The University of Sheffield, University of York) and Zenodo (CERN European Organization for Nuclear Research).

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.

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