Salem Said

813 citations
21 papers · 452 · h-index 8

Impact in

Papers in

Salem Said

18 papers receiving 445 citations

Peers

Salem Said
Comparison fields: 5 of 65
  • Cognitive Neuroscience 254
  • Human-Computer Interaction 61
  • Signal Processing 89
  • Cellular and Molecular Neuroscience 67
  • Computer Vision and Pattern Recognition 77
Replace Yuanyuan Shen with:
Yuanyuan Shen China
Atsunori Kanemura Japan
Clive Cheong Took United Kingdom
Yanli Zhang China
Hyoung-Nam Kim South Korea
P. S. Sathidevi India
Ana Rita Teixeira Portugal
Jaakko Särelä Finland
Saideh Ferdowsi United Kingdom
David J. Anderson United States
Salem Said relative to Yuanyuan Shen China Yuanyuan Shen's profile →
Citations per field
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Yuanyuan Shen · 1×
Citations per year

Countries citing papers authored by Salem Said

Since Specialization
Citations

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

Fields of papers citing papers by Salem Said

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Salem Said, 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 Salem Said Line = papers co-authored together Salem Said links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017276
2 200865
3 201624
4 201511
5 201210
6 201510
7 20139
8 20188
9 20187
10 20167
11 20146
12 20106
13 20235
14 20223
15 20122
16 20161
17 20151
18 20091
19 20090
20 20130

About Salem Said

Salem Said is a scholar working on Computer Vision and Pattern Recognition, Geometry and Topology, Artificial Intelligence, Statistics and Probability and Applied Mathematics, having authored 21 papers that have together received 452 indexed citations. Recurring topics across this work include Morphological variations and asymmetry (6 papers), Image Retrieval and Classification Techniques (5 papers), Bayesian Methods and Mixture Models (5 papers), Stochastic processes and financial applications (3 papers), Remote-Sensing Image Classification (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Mathematical Analysis and Transform Methods (3 papers) and Control Systems and Identification (2 papers). The work is most often cited by research in Cognitive Neuroscience (254 citations), Human-Computer Interaction (61 citations), Signal Processing (89 citations), Cellular and Molecular Neuroscience (67 citations) and Computer Vision and Pattern Recognition (77 citations). Salem Said has collaborated with scholars based in France, Australia and Romania. Frequent co-authors include Yannick Berthoumieu, Paolo Zanini, Marco Congedo, Christian Jutten, Nicolas Le Bihan, Stephen J. Sangwine, Jonathan H. Manton, Lionel Bombrun, Marc Donias and Jean‐Pierre da Costa. Their work appears in journals such as IEEE Transactions on Information Theory, Pattern Recognition Letters, Signal Processing, IEEE Transactions on Biomedical Engineering and IEEE Signal Processing Letters.

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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