Rahim Saeidi

1.7k citations
65 papers · 1.2k · h-index 21

Impact in

Papers in

Rahim Saeidi

65 papers receiving 1.1k citations

Peers

Rahim Saeidi
Comparison fields: 5 of 69
  • Signal Processing 1.1k
  • Artificial Intelligence 848
  • Computational Mechanics 234
  • Computer Vision and Pattern Recognition 127
  • Experimental and Cognitive Psychology 72
Replace Christophe Veaux with:
Christophe Veaux France
Hong-Goo Kang South Korea
Chanwoo Kim South Korea
Xu Shao United Kingdom
A. Alwan United States
Cassia Valentini-Botinhao United Kingdom
Roland Maas Germany
Soundararajan Srinivasan United States
Shinji Takaki Japan
Hans‐Günter Hirsch Germany
Rahim Saeidi relative to Christophe Veaux France Christophe Veaux's profile →
Citations per field
00.5×3.7×
Christophe Veaux · 1×
Citations per year

Countries citing papers authored by Rahim Saeidi

Since Specialization
Citations

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

Fields of papers citing papers by Rahim Saeidi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rahim Saeidi. 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 Rahim Saeidi. The network helps show where Rahim Saeidi may publish in the future.

Co-authors

The 25 scholars most cited alongside Rahim Saeidi, 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 Rahim Saeidi Line = papers co-authored together Rahim Saeidi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012103
2 201384
3 201684
4 201363
5 201358
6 201254
7 201054
8 201350
9 201233
10 201630
11 201026
12 201026
13 201424
14 201223
15 201822
16 201022
17 201021
18 201321
19 201521
20 201521

About Rahim Saeidi

Rahim Saeidi is a scholar working on Signal Processing, Artificial Intelligence, Computational Mechanics, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 65 papers that have together received 1.2k indexed citations. Recurring topics across this work include Speech and Audio Processing (62 papers), Speech Recognition and Synthesis (55 papers), Music and Audio Processing (33 papers), Blind Source Separation Techniques (14 papers), Advanced Adaptive Filtering Techniques (11 papers), Advanced Data Compression Techniques (4 papers), Phonetics and Phonology Research (2 papers) and Face recognition and analysis (2 papers). The work is most often cited by research in Signal Processing (1.1k citations), Artificial Intelligence (848 citations), Computational Mechanics (234 citations), Computer Vision and Pattern Recognition (127 citations) and Experimental and Cognitive Psychology (72 citations). Rahim Saeidi has collaborated with scholars based in Finland, Netherlands and United States. Frequent co-authors include Pejman Mowlaee, Tomi Kinnunen, David A. van Leeuwen, Paavo Alku, Yannis Stylianou, Jouni Pohjalainen, Maria Hansson-Sandsten, Rainer Martin, Taufiq Hasan and John H. L. Hansen. Their work appears in journals such as IEEE Signal Processing Letters, IEEE Transactions on Audio Speech and Language Processing, Computer Speech & Language, Speech Communication and IEEE/ACM Transactions on Audio Speech and Language 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.

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