Shervan Fekri-Ershad

1.3k citations
26 papers · 854 indexed · h-index 19

Shervan Fekri-Ershad

24 papers receiving 822 citations

Peers

Shervan Fekri-Ershad
Comparison fields: 5 of 119
  • Computer Vision and Pattern Recognition 434
  • Media Technology 147
  • Industrial and Manufacturing Engineering 133
  • Artificial Intelligence 215
  • Radiology, Nuclear Medicine and Imaging 111
Replace Saadat Hanif Dar with:
Saadat Hanif Dar Pakistan
Zhanghan Ke Hong Kong
Diganta Misra India
Bushra Zafar Pakistan
Shoubhik Debnath United States
Yingtian Zou Singapore
Azizi Abdullah Malaysia
Zhuang Liu China
P. Ganesan India
Chirag Patel India
Shervan Fekri-Ershad relative to Saadat Hanif Dar Pakistan Saadat Hanif Dar's profile →
Citations per field
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Citations per year

Countries citing papers authored by Shervan Fekri-Ershad

Since Specialization
Citations

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

Fields of papers citing papers by Shervan Fekri-Ershad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shervan Fekri-Ershad. 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 Shervan Fekri-Ershad. The network helps show where Shervan Fekri-Ershad may publish in the future.

Co-authorship network

The 7 scholars most cited alongside Shervan Fekri-Ershad, 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 Shervan Fekri-Ershad Line = papers co-authored together Shervan Fekri-Ershad links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20253
2 20240
3 202436
4 20241
5 202351
6 20227
7 20225
8 202260
9 202253
10 202153
11 202034
12 201930
13 201932
14 201936
15 201723
16 201738
17 201730
18 201329
19 201211
20 201218

About Shervan Fekri-Ershad

Shervan Fekri-Ershad is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Industrial and Manufacturing Engineering, Biophysics and Analytical Chemistry, having authored 26 papers that have together received 854 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (11 papers), Advanced Image and Video Retrieval Techniques (8 papers), Industrial Vision Systems and Defect Detection (6 papers), AI in cancer detection (5 papers), Digital Imaging for Blood Diseases (4 papers), Surface Roughness and Optical Measurements (4 papers), Remote-Sensing Image Classification (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (434 citations), Media Technology (147 citations), Industrial and Manufacturing Engineering (133 citations), Artificial Intelligence (215 citations) and Radiology, Nuclear Medicine and Imaging (111 citations). Shervan Fekri-Ershad has collaborated with scholars based in Iran, Australia and Italy. Frequent co-authors include Farshad Tajeripour, S. Ramakrishnan, Loris Nanni, Alireza Alaei, Azita Yazdani, Mohammadreza Ramezanpour and Behrang Barekatain. Their work appears in journals such as Multimedia Tools and Applications, Computational Intelligence and Neuroscience, Indian Journal of Science and Technology, Expert Systems with Applications and Arabian Journal for Science and Engineering.

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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