Talha Meraj

945 total citations
24 papers, 576 citations indexed

About

Talha Meraj is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Talha Meraj has authored 24 papers receiving a total of 576 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 7 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Talha Meraj's work include Misinformation and Its Impacts (4 papers), COVID-19 diagnosis using AI (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Talha Meraj is often cited by papers focused on Misinformation and Its Impacts (4 papers), COVID-19 diagnosis using AI (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Talha Meraj collaborates with scholars based in Pakistan, United Kingdom and Saudi Arabia. Talha Meraj's co-authors include Hafiz Tayyab Rauf, Saeed Ur Rehman, Amerah Alabrah, Robertas Damaševičius, Rabbia Mahum, Mohammed A. El-Meligy, Ahmed M. El‐Sherbeeny, Hashem Alyami, M. Sultan Zia and Aun Irtaza and has published in prestigious journals such as Sensors, Applied Sciences and Neural Computing and Applications.

In The Last Decade

Talha Meraj

22 papers receiving 551 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Talha Meraj Pakistan	13	240	219	122	60	57	24	576
Sheeraz Akram Pakistan	17	237 1.0×	222 1.0×	176 1.4×	140 2.3×	31 0.5×	52	635
Surbhi Gupta India	15	188 0.8×	268 1.2×	83 0.7×	39 0.7×	10 0.2×	24	563
Preetham Kumar India	11	218 0.9×	96 0.4×	201 1.6×	16 0.3×	35 0.6×	40	405
N. Veeranjaneyulu India	12	278 1.2×	184 0.8×	240 2.0×	22 0.4×	29 0.5×	34	578
Jyostna Devi Bodapati India	13	314 1.3×	199 0.9×	267 2.2×	23 0.4×	32 0.6×	37	621
Awais Mehmood Pakistan	9	158 0.7×	195 0.9×	225 1.8×	16 0.3×	12 0.2×	23	549
Liangliang Liu China	8	117 0.5×	160 0.7×	175 1.4×	21 0.3×	22 0.4×	21	481
Enas M. F. El Houby Egypt	11	270 1.1×	347 1.6×	111 0.9×	32 0.5×	21 0.4×	17	509
Somsak Choomchuay Thailand	11	121 0.5×	132 0.6×	134 1.1×	37 0.6×	4 0.1×	60	349

Countries citing papers authored by Talha Meraj

Since Specialization

Citations

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

Fields of papers citing papers by Talha Meraj

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Talha Meraj

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

All Works

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20 of 20 papers shown

Kamran, Muhammad, Saeed Ur Rehman, Talha Meraj, Khalid A. Alnowibet, & Hafiz Tayyab Rauf. (2025). Correction: Kamran et al. Camouflage Object Segmentation Using an Optimized Deep-Learning Approach. Mathematics 2022, 10, 4219. Mathematics. 13(7). 1058–1058.

Meraj, Talha, et al.. (2024). An Efficient Text-Mining Framework of Automatic Essay Grading Using Discourse Macrostructural and Statistical Lexical Features. SAGE Open. 14(4).

Alabrah, Amerah, et al.. (2023). Attention-Enriched Mini-BERT Fake News Analyzer Using the Arabic Language. Future Internet. 15(2). 44–44. 13 indexed citations

Alabrah, Amerah, et al.. (2023). Semantic Features-Based Discourse Analysis Using Deceptive and Real Text Reviews. Information. 14(1). 34–34. 4 indexed citations

Zia, M. Sultan, et al.. (2023). A Minority Class Balanced Approach Using the DCNN-LSTM Method to Detect Human Wrist Fracture. Life. 13(1). 133–133. 16 indexed citations

Meraj, Talha, Muhammad Sharif, Mudassar Raza, et al.. (2023). Computer vision-based plants phenotyping: A comprehensive survey. iScience. 27(1). 108709–108709. 10 indexed citations

Alabrah, Amerah, et al.. (2023). English Language Learning via YouTube: An NLP-Based Analysis of Users’ Comments. Computers. 12(2). 24–24. 8 indexed citations

Liaqat, Hannan Bin, et al.. (2023). Identification and Classification of Lungs Focal Opacity Using CNN Segmentation and Optimal Feature Selection. Computational Intelligence and Neuroscience. 2023(1). 6357252–6357252. 2 indexed citations

Zia, M. Sultan, et al.. (2023). Epileptic Patient Activity Recognition System Using Extreme Learning Machine Method. Biomedicines. 11(3). 816–816. 13 indexed citations

10.

Alabrah, Amerah, et al.. (2022). Discourse analysis based credibility checks to online reviews using deep learning based discourse markers. Computer Speech & Language. 78. 101450–101450. 3 indexed citations

11.

Kamran, Muhammad, Saeed Ur Rehman, Talha Meraj, Khalid A. Alnowibet, & Hafiz Tayyab Rauf. (2022). Camouflage Object Segmentation Using an Optimized Deep-Learning Approach. Mathematics. 10(22). 4219–4219. 6 indexed citations

12.

Alharbi, Abdullah, Majid Alshammari, Amerah Alabrah, et al.. (2022). A Novel text2IMG Mechanism of Credit Card Fraud Detection: A Deep Learning Approach. Electronics. 11(5). 756–756. 49 indexed citations

13.

Albahli, Saleh, Talha Meraj, Chinmay Chakraborty, & Hafiz Tayyab Rauf. (2022). AI-driven deep and handcrafted features selection approach for Covid-19 and chest related diseases identification. Multimedia Tools and Applications. 81(26). 37569–37589. 6 indexed citations

14.

Alabrah, Amerah, et al.. (2022). Gulf Countries’ Citizens’ Acceptance of COVID-19 Vaccines—A Machine Learning Approach. Mathematics. 10(3). 467–467. 12 indexed citations

15.

Huang, Kai, et al.. (2022). A novel CAPTCHA solver framework using deep skipping Convolutional Neural Networks. PeerJ Computer Science. 8. e879–e879. 7 indexed citations

16.

Mostafa, Almetwally M., et al.. (2021). Guava Disease Detection Using Deep Convolutional Neural Networks: A Case Study of Guava Plants. Applied Sciences. 12(1). 239–239. 48 indexed citations

17.

Majeed, Fiaz, et al.. (2021). A Lightweight Approach for Skin Lesion Detection Through Optimal Features Fusion. Computers, materials & continua/Computers, materials & continua (Print). 70(1). 1617–1630. 18 indexed citations

18.

Mahum, Rabbia, et al.. (2021). A Novel Hybrid Approach Based on Deep CNN to Detect Glaucoma Using Fundus Imaging. Electronics. 11(1). 26–26. 56 indexed citations

19.

Zia, M. Sultan, Talha Meraj, Hafiz Tayyab Rauf, et al.. (2021). A Self-Activated CNN Approach for Multi-Class Chest-Related COVID-19 Detection. Applied Sciences. 11(19). 9023–9023. 49 indexed citations

20.

Meraj, Talha, Hafiz Tayyab Rauf, Saliha Zahoor, et al.. (2020). Lung nodules detection using semantic segmentation and classification with optimal features. Neural Computing and Applications. 33(17). 10737–10750. 65 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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