Saeed Kermani

36 papers receiving 590 citations

Peers

Saeed Kermani
Comparison fields: 5 of 98
  • Biophysics 91
  • Ophthalmology 125
  • Computer Vision and Pattern Recognition 245
  • Radiology, Nuclear Medicine and Imaging 264
  • Biomedical Engineering 205
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Amin Katouzian Germany
Radim Kolář Czechia
Nancy M. Salem Egypt
Adrián Colomer Spain
Tahir Mahmood South Korea
Haidar Almubarak Saudi Arabia
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Shafiullah Soomro South Korea
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Citations per year

Countries citing papers authored by Saeed Kermani

Since Specialization
Citations

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

Fields of papers citing papers by Saeed Kermani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015121
2 201394
3
A review of algorithms for segmentation of optical coherence tomography from retina.
201382
4 201660
5 201730
6 201428
7 201524
8 202023
9
Enhanced Recognition of Acute Lymphoblastic Leukemia Cells in Microscopic Images based on Feature Reduction using Principle Component Analysis
201518
10 201116
11 200914
12 201810
13 201310
14 201610
15 20199
16 20208
17 20108
18
Effect of Extremely Low-Frequency (50 Hz) Field on Proliferation Rate of Human Adipose-Derived Mesenchymal Stem Cells
20137
19 20185
20 20244

About Saeed Kermani

Saeed Kermani is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Cognitive Neuroscience, having authored 40 papers that have together received 608 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), EEG and Brain-Computer Interfaces (5 papers), ECG Monitoring and Analysis (5 papers), Cell Image Analysis Techniques (4 papers), Advanced MRI Techniques and Applications (4 papers), Digital Imaging for Blood Diseases (4 papers), AI in cancer detection (4 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Biophysics (91 citations), Ophthalmology (125 citations), Computer Vision and Pattern Recognition (245 citations), Radiology, Nuclear Medicine and Imaging (264 citations) and Biomedical Engineering (205 citations). Saeed Kermani has collaborated with scholars based in Iran, United States and Sweden. Frequent co-authors include Rahele Kafieh, Hossein Rabbani, Ardeshir Talebi, Daryoush Shahbazi‐Gahrouei, Mohammadreza Sehhati, Mahnaz Etehadtavakol, Shahnaz Razavi, Saeed Karbasi, Marzieh Salimi and Hamid Sanei. Their work appears in journals such as Computerized Medical Imaging and Graphics, Physica Medica, Journal of Medical Signals & Sensors, IEEE Journal of Biomedical and Health Informatics and Journal of Applied Sciences.

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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