Zahid Ullah

1.7k total citations · 2 hit papers
26 papers, 1.2k citations indexed

About

Zahid Ullah is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Zahid Ullah has authored 26 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 7 papers in Neurology. Recurrent topics in Zahid Ullah's work include Advanced Neural Network Applications (9 papers), Brain Tumor Detection and Classification (7 papers) and Medical Image Segmentation Techniques (5 papers). Zahid Ullah is often cited by papers focused on Advanced Neural Network Applications (9 papers), Brain Tumor Detection and Classification (7 papers) and Medical Image Segmentation Techniques (5 papers). Zahid Ullah collaborates with scholars based in South Korea, Pakistan and Saudi Arabia. Zahid Ullah's co-authors include Jeonghwan Gwak, Jaeyong Kang, Muzammil Khan, Salman Raza Naqvi, Muhammad Usman, Muhammad Nouman Aslam Khan, Muhammad Taqi Mehran, Su-Hyun Lee, Moongu Jeon and Wasif Farooq and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioresource Technology and Scientific Reports.

In The Last Decade

Zahid Ullah

23 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers

2021 378 citations Jaeyong Kang, Zahid Ullah et al. Sensors profile →
Applications of machine learning in thermochemical conversion of biomass-A review

2022 146 citations Muzammil Khan, Salman Raza Naqvi et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zahid Ullah South Korea	12	503	435	366	284	268	26	1.2k
Mohamed Arselene Ayari Qatar	24	123 0.2×	233 0.5×	332 0.9×	603 2.1×	405 1.5×	65	1.9k
Chandran Venkatesan India	11	194 0.4×	118 0.3×	312 0.9×	146 0.5×	79 0.3×	21	964
M. G. Sumithra India	15	242 0.5×	155 0.4×	311 0.8×	168 0.6×	135 0.5×	49	911
Mohd Asyraf Zulkifley Malaysia	21	38 0.1×	485 1.1×	251 0.7×	442 1.6×	198 0.7×	128	1.9k
Xiongfei Li China	21	73 0.1×	576 1.3×	187 0.5×	89 0.3×	167 0.6×	107	1.2k
Yue Zhou China	16	44 0.1×	372 0.9×	300 0.8×	253 0.9×	121 0.5×	52	920
Khairunnisa Hasikin‬ Malaysia	19	28 0.1×	272 0.6×	132 0.4×	188 0.7×	156 0.6×	94	1.0k
Saddaf Rubab Pakistan	14	42 0.1×	125 0.3×	146 0.4×	95 0.3×	87 0.3×	51	591
Muhammad Owais Pakistan	20	102 0.2×	428 1.0×	318 0.9×	485 1.7×	115 0.4×	94	1.2k

Countries citing papers authored by Zahid Ullah

Since Specialization

Citations

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

Fields of papers citing papers by Zahid Ullah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zahid Ullah

This figure shows the co-authorship network connecting the top 25 collaborators of Zahid Ullah. A scholar is included among the top collaborators of Zahid Ullah 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 Zahid Ullah. Zahid Ullah 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

Ullah, Zahid, et al.. (2025). Systematic Integration of Attention Modules into CNNs for Accurate and Generalizable Medical Image Classification. Mathematics. 13(22). 3728–3728.

Ullah, Zahid & Jihie Kim. (2025). Anatomically accurate cardiac segmentation using Dense Associative Networks. Engineering Applications of Artificial Intelligence. 162. 112742–112742.

Ullah, Zahid, et al.. (2024). Multi-teacher cross-modal distillation with cooperative deep supervision fusion learning for unimodal segmentation. Knowledge-Based Systems. 297. 111854–111854. 9 indexed citations

Mahmood, Tahir, Muhammad Zubair, Zahid Ullah, et al.. (2024). Computer-Aided Diagnosis in Spontaneous Abortion: A Histopathology Dataset and Benchmark for Products of Conception. Diagnostics. 14(24). 2877–2877. 2 indexed citations

Ullah, Zahid, Iftikhar Ahmad, Farooq Ahmad, et al.. (2024). Artificial intelligence assisted prediction of optimum operating conditions of shell and tube heat exchangers: A grey‐box approach. CAAI Transactions on Intelligence Technology. 10(2). 349–358. 6 indexed citations

Farooq, Muhammad Umar, Zahid Ullah, & Jeonghwan Gwak. (2023). Residual attention based uncertainty-guided mean teacher model for semi-supervised breast masses segmentation in 2D ultrasonography. Computerized Medical Imaging and Graphics. 104. 102173–102173. 19 indexed citations

Ullah, Zahid, Muhammad Usman, Siddique Latif, & Jeonghwan Gwak. (2023). Densely attention mechanism based network for COVID-19 detection in chest X-rays. Scientific Reports. 13(1). 261–261. 40 indexed citations

Farooq, Muhammad Umar, Zahid Ullah, Asifullah Khan, & Jeonghwan Gwak. (2023). DC-AAE: Dual channel adversarial autoencoder with multitask learning for KL-grade classification in knee radiographs. Computers in Biology and Medicine. 167. 107570–107570. 8 indexed citations

Ullah, Zahid, Muhammad Usman, Siddique Latif, Asifullah Khan, & Jeonghwan Gwak. (2023). SSMD-UNet: semi-supervised multi-task decoders network for diabetic retinopathy segmentation. Scientific Reports. 13(1). 9087–9087. 26 indexed citations

10.

Ullah, Zahid, Muhammad Usman, & Jeonghwan Gwak. (2023). MTSS-AAE: Multi-task semi-supervised adversarial autoencoding for COVID-19 detection based on chest X-ray images. Expert Systems with Applications. 216. 119475–119475. 38 indexed citations

11.

Khan, Muzammil, Zahid Ullah, Ondřej Mašek, Salman Raza Naqvi, & Muhammad Nouman Aslam Khan. (2022). Artificial neural networks for the prediction of biochar yield: A comparative study of metaheuristic algorithms. Bioresource Technology. 355. 127215–127215. 89 indexed citations

12.

Ullah, Zahid, Muhammad Usman, Moongu Jeon, & Jeonghwan Gwak. (2022). Cascade multiscale residual attention CNNs with adaptive ROI for automatic brain tumor segmentation. Information Sciences. 608. 1541–1556. 86 indexed citations

13.

Kang, Jaeyong, Zahid Ullah, & Jeonghwan Gwak. (2021). MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers. Sensors. 21(6). 2222–2222. 378 indexed citations breakdown →

14.

Khan, Muzammil, Muhammad Taqi Mehran, Zeeshan Haq, et al.. (2021). Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review. Expert Systems with Applications. 185. 115695–115695. 130 indexed citations

15.

Ho, Thi Kieu Khanh, Minhee Kim, Zahid Ullah, et al.. (2021). Improving the multi‐class classification of Alzheimer’s disease with machine learning‐based techniques: An EEG‐fNIRS hybridization study. Alzheimer s & Dementia. 17(S7). 3 indexed citations

16.

Ullah, Zahid, et al.. (2020). A hybrid image enhancement based brain MRI images classification technique. Medical Hypotheses. 143. 109922–109922. 98 indexed citations

17.

Khattak, Aamer Ali, et al.. (2020). Nasal carriage of highly resistant methicillin resistant Staphylococcus aureus (MRSA) strains by hospital staff in Hazara region of Pakistan. SHILAP Revista de lepidopterología. 71(1(A)). 1–12. 4 indexed citations

18.

Ullah, Zahid, et al.. (2020). Critical Analysis of Brain Magnetic Resonance Images Tumor Detection and Classification Techniques. International Journal of Advanced Computer Science and Applications. 11(1). 2 indexed citations

19.

Ullah, Zahid, et al.. (2020). Histogram Equalization based Enhancement and MR Brain Image Skull Stripping using Mathematical Morphology. International Journal of Advanced Computer Science and Applications. 11(3). 6 indexed citations

20.

Ullah, Zahid, et al.. (2019). Enhanced feature extraction technique for brain MRI classification based on Haar wavelet and statistical moments. International Journal of ADVANCED AND APPLIED SCIENCES. 6(7). 89–98. 16 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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