Saad Sirohey

2.9k total citations · 1 hit paper
10 papers, 2.0k citations indexed

About

Saad Sirohey is a scholar working on Computer Vision and Pattern Recognition, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Saad Sirohey has authored 10 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 3 papers in Oncology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Saad Sirohey's work include Colorectal Cancer Screening and Detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Biometric Identification and Security (2 papers). Saad Sirohey is often cited by papers focused on Colorectal Cancer Screening and Detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Biometric Identification and Security (2 papers). Saad Sirohey collaborates with scholars based in United States and Spain. Saad Sirohey's co-authors include Charles L. Wilson, Rama Chellappa, Azriel Rosenfeld, Paulo R. S. Mendonça, Rahul Bhotika, James V. Miller, Ricardo S. Avila, Rebecca Brown, Fei Zhao and Gopal Avinash and has published in prestigious journals such as Proceedings of the IEEE, Pattern Recognition and Lecture notes in computer science.

In The Last Decade

Saad Sirohey

9 papers receiving 1.7k citations

Hit Papers

Human and machine recognition of faces: a survey 1995 2026 2005 2015 1995 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Saad Sirohey United States 6 1.8k 485 234 185 151 10 2.0k
Rein-Lien Hsu United States 8 1.3k 0.8× 303 0.6× 117 0.5× 234 1.3× 75 0.5× 10 1.6k
Bo Cao China 15 1.1k 0.6× 364 0.8× 172 0.7× 76 0.4× 279 1.8× 36 1.7k
D.L. Swets United States 7 1.2k 0.7× 313 0.6× 244 1.0× 48 0.3× 229 1.5× 9 1.4k
Xiaohua Zhang China 12 940 0.5× 199 0.4× 244 1.0× 65 0.4× 84 0.6× 36 1.2k
Jaesik Min United States 7 1.7k 0.9× 697 1.4× 132 0.6× 31 0.2× 190 1.3× 9 1.9k
Xilin Chen China 10 929 0.5× 241 0.5× 100 0.4× 107 0.6× 87 0.6× 18 1.1k
William J. Worek United States 5 1.7k 1.0× 788 1.6× 117 0.5× 35 0.2× 146 1.0× 6 2.0k
P. Kakumanu United States 8 609 0.3× 140 0.3× 44 0.2× 174 0.9× 71 0.5× 11 830
Alberto Albiol Spain 13 732 0.4× 177 0.4× 89 0.4× 62 0.3× 84 0.6× 51 892
Krešimir Delač Croatia 11 858 0.5× 476 1.0× 103 0.4× 38 0.2× 203 1.3× 27 1.2k

Countries citing papers authored by Saad Sirohey

Since Specialization
Citations

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

Fields of papers citing papers by Saad Sirohey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saad Sirohey

This figure shows the co-authorship network connecting the top 25 collaborators of Saad Sirohey. A scholar is included among the top collaborators of Saad Sirohey based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Saad Sirohey. Saad Sirohey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Avinash, Gopal, et al.. (2013). Quantitative measurement of MR cortical atrophy: MR brain surface intensity model (BSIM) and group and individual cortical thinning studies. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8672. 86720E–86720E. 1 indexed citations
2.
Mendonça, Paulo R. S., et al.. (2008). Detection of Polyps via Shape and Appearance Modeling. SMARTech Repository (Georgia Institute of Technology). 2 indexed citations
3.
Mendonça, Paulo R. S., et al.. (2007). A Probabilistic Model for Haustral Curvatures with Applications to Colon CAD. Lecture notes in computer science. 10(Pt 2). 420–427. 3 indexed citations
4.
Bhotika, Rahul, et al.. (2006). Part-Based Local Shape Models for Colon Polyp Detection. Lecture notes in computer science. 9(Pt 2). 479–486. 11 indexed citations
5.
Mendonça, Paulo R. S., et al.. (2005). Model-Based Analysis of Local Shape for Lesion Detection in CT Scans. Lecture notes in computer science. 8(Pt 1). 688–695. 20 indexed citations
6.
Sirohey, Saad, et al.. (2002). A method of detecting and tracking irises and eyelids in video. Pattern Recognition. 35(6). 1389–1401. 83 indexed citations
7.
Sirohey, Saad & Azriel Rosenfeld. (2001). Eye detection in a face image using linear and nonlinear filters. Pattern Recognition. 34(7). 1367–1391. 78 indexed citations
8.
Sirohey, Saad & Azriel Rosenfeld. (1999). Eye detection and tracking. 5 indexed citations
9.
Sirohey, Saad. (1998). Human Face Segmentation and Identification. Digital Repository at the University of Maryland (University of Maryland College Park). 60 indexed citations
10.
Chellappa, Rama, Charles L. Wilson, & Saad Sirohey. (1995). Human and machine recognition of faces: a survey. Proceedings of the IEEE. 83(5). 705–741. 1730 indexed citations breakdown →

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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