Samar M. Alqhtani

887 total citations
45 papers, 517 citations indexed

About

Samar M. Alqhtani is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Samar M. Alqhtani has authored 45 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 9 papers in Computer Networks and Communications. Recurrent topics in Samar M. Alqhtani's work include Brain Tumor Detection and Classification (8 papers), Advanced Neural Network Applications (8 papers) and Digital Imaging for Blood Diseases (4 papers). Samar M. Alqhtani is often cited by papers focused on Brain Tumor Detection and Classification (8 papers), Advanced Neural Network Applications (8 papers) and Digital Imaging for Blood Diseases (4 papers). Samar M. Alqhtani collaborates with scholars based in Saudi Arabia, Pakistan and Poland. Samar M. Alqhtani's co-authors include Muhammad Irfan, Tariq Ali, Ahmad Shaf, Abdullah A. Asiri, Saifur Rahman, Muhammad Aamir, Adam Głowacz, Suhuai Luo, Alzubair Hassan and Rafik Hamza and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Access.

In The Last Decade

Samar M. Alqhtani

43 papers receiving 482 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samar M. Alqhtani Saudi Arabia 14 178 151 134 97 82 45 517
Hadeel Alsolai Saudi Arabia 12 199 1.1× 50 0.3× 113 0.8× 105 1.1× 81 1.0× 32 604
Muhammad Assam Pakistan 11 134 0.8× 57 0.4× 112 0.8× 69 0.7× 50 0.6× 35 401
Yousef Alhwaiti Saudi Arabia 10 141 0.8× 34 0.2× 100 0.7× 87 0.9× 68 0.8× 22 385
Debanjan Konar India 11 221 1.2× 32 0.2× 77 0.6× 75 0.8× 54 0.7× 31 433
Chuin-Mu Wang Taiwan 11 162 0.9× 58 0.4× 174 1.3× 42 0.4× 31 0.4× 41 510
Shahid Karim China 16 108 0.6× 42 0.3× 284 2.1× 53 0.5× 84 1.0× 46 633
Shahab Wahhab Kareem Iraq 13 190 1.1× 38 0.3× 90 0.7× 39 0.4× 32 0.4× 58 409
Nadhem Nemri Saudi Arabia 12 168 0.9× 28 0.2× 79 0.6× 54 0.6× 105 1.3× 50 431
Balasubramanian Prabhu Kavin India 11 171 1.0× 34 0.2× 65 0.5× 50 0.5× 162 2.0× 40 458
P. Varalakshmi India 12 256 1.4× 43 0.3× 129 1.0× 42 0.4× 161 2.0× 91 590

Countries citing papers authored by Samar M. Alqhtani

Since Specialization
Citations

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

Fields of papers citing papers by Samar M. Alqhtani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Samar M. Alqhtani. 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 Samar M. Alqhtani. The network helps show where Samar M. Alqhtani may publish in the future.

Co-authorship network of co-authors of Samar M. Alqhtani

This figure shows the co-authorship network connecting the top 25 collaborators of Samar M. Alqhtani. A scholar is included among the top collaborators of Samar M. Alqhtani 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 Samar M. Alqhtani. Samar M. Alqhtani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Alqhtani, Samar M., et al.. (2024). Contrast Normalization Strategies in Brain Tumor Imaging: From Preprocessing to Classification. Computer Modeling in Engineering & Sciences. 140(2). 1539–1562. 2 indexed citations
3.
Shaf, Ahmad, Tariq Ali, Samar M. Alqhtani, et al.. (2024). A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough. IEEE Access. 12. 41542–41556. 5 indexed citations
4.
Alqhtani, Samar M., Toufique Ahmed Soomro, Ahmed Ali, et al.. (2024). Improved Brain Tumor Segmentation and Classification in Brain MRI With FCM-SVM: A Diagnostic Approach. IEEE Access. 12. 61312–61335. 26 indexed citations
5.
Saeed, Muhammad, et al.. (2024). Smart Healthcare: A Dynamic Blockchain-Based Trust Management Model Using Subarray Algorithm. IEEE Access. 12. 49449–49463. 2 indexed citations
6.
Mastoi, Qurat-ul-ain, Ali Alqahtani, Sultan Almakdi, et al.. (2024). Heart patient health monitoring system using invasive and non-invasive measurement. Scientific Reports. 14(1). 9614–9614. 4 indexed citations
7.
Asiri, Abdullah A., Ahmad Shaf, Tariq Ali, et al.. (2023). Exploring the Power of Deep Learning: Fine-Tuned Vision Transformer for Accurate and Efficient Brain Tumor Detection in MRI Scans. Diagnostics. 13(12). 2094–2094. 38 indexed citations
8.
Ali, Usman, Javed Ferzund, Ahmad Shaf, et al.. (2023). Enhanced Adaptive Brain-Computer Interface Approach for Intelligent Assistance to Disabled Peoples. Computer Systems Science and Engineering. 46(2). 1355–1369. 1 indexed citations
9.
Asiri, Abdullah A., Ahmad Shaf, Tariq Ali, et al.. (2023). Brain Tumor Detection and Classification Using Fine-Tuned CNN with ResNet50 and U-Net Model: A Study on TCGA-LGG and TCIA Dataset for MRI Applications. Life. 13(7). 1449–1449. 50 indexed citations
10.
Irfan, Muhammad, et al.. (2023). AQSA: Aspect-Based Quality Sentiment Analysis for Multi-Labeling with Improved ResNet Hybrid Algorithm. Electronics. 12(6). 1298–1298. 7 indexed citations
11.
Asiri, Abdullah A., Muhammad Aamir, Tariq Ali, et al.. (2023). Next-Gen brain tumor classification: pioneering with deep learning and fine-tuned conditional generative adversarial networks. PeerJ Computer Science. 9. e1667–e1667. 5 indexed citations
12.
Irfan, Muhammad, et al.. (2023). An intelligent framework to measure the effects of COVID-19 on the mental health of medical staff. PLoS ONE. 18(6). e0286155–e0286155. 3 indexed citations
13.
Irfan, Muhammad, Ahmad Shaf, Tariq Ali, et al.. (2023). Effectiveness of Deep Learning Models for Brain Tumor Classification and Segmentation. Computers, materials & continua/Computers, materials & continua (Print). 76(1). 711–729. 2 indexed citations
14.
Irfan, Muhammad, Faisal Althobiani, Abdullah Alwadie, et al.. (2022). Condition monitoring of water pump bearings using ensemble classifier. Advances in Mechanical Engineering. 14(3). 8 indexed citations
15.
Almalki, Yassir Edrees, Toufique Ahmed Soomro, Ahmed Ali, et al.. (2022). Enhancement of Medical Images through an Iterative McCann Retinex Algorithm: A Case of Detecting Brain Tumor and Retinal Vessel Segmentation. Applied Sciences. 12(16). 8243–8243. 9 indexed citations
16.
Ferzund, Javed, et al.. (2022). 360° Retail Business Analytics by Adopting Hybrid Machine Learning and a Business Intelligence Approach. Sustainability. 14(19). 11942–11942. 5 indexed citations
17.
Alqahtani, Ali, et al.. (2022). A Transfer Learning Based Approach for COVID-19 Detection Using Inception-v4 Model. Intelligent Automation & Soft Computing. 35(2). 1721–1736. 5 indexed citations
18.
Aamir, Muhammad, Tariq Ali, Muhammad Irfan, et al.. (2021). Natural Disasters Intensity Analysis and Classification Based on Multispectral Images Using Multi-Layered Deep Convolutional Neural Network. Sensors. 21(8). 2648–2648. 32 indexed citations
19.
Yasin, Sana, Tariq Ali, Umar Draz, et al.. (2021). Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture. Sensors. 21(20). 6933–6933. 13 indexed citations
20.
Alqhtani, Samar M., et al.. (2017). A multiple kernel learning based fusion for earthquake detection from multimedia twitter data. Multimedia Tools and Applications. 77(10). 12519–12532. 2 indexed citations

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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