Saeeda Naz

4.6k total citations · 1 hit paper
60 papers, 2.1k citations indexed

About

Saeeda Naz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Saeeda Naz has authored 60 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Computer Vision and Pattern Recognition, 23 papers in Artificial Intelligence and 22 papers in Media Technology. Recurrent topics in Saeeda Naz's work include Handwritten Text Recognition Techniques (35 papers), Vehicle License Plate Recognition (19 papers) and Image Processing and 3D Reconstruction (14 papers). Saeeda Naz is often cited by papers focused on Handwritten Text Recognition Techniques (35 papers), Vehicle License Plate Recognition (19 papers) and Image Processing and 3D Reconstruction (14 papers). Saeeda Naz collaborates with scholars based in Pakistan, Saudi Arabia and Australia. Saeeda Naz's co-authors include Imran Razzak, Arshia Rehman, Muhammad Imran, Saad Bin Ahmed, Faiza Akram, Arif Iqbal Umar, Riaz Ahmad, Syed Hamad Shirazi, Abida Ashraf and Ahmad Zaib and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Saeeda Naz

59 papers receiving 1.9k 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.

A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning

2019 432 citations Arshia Rehman, Saeeda Naz et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Saeeda Naz Pakistan	23	1.4k	711	604	546	245	60	2.1k
Vishnuvarthanan Govindaraj India	17	608 0.4×	506 0.7×	92 0.2×	542 1.0×	373 1.5×	91	1.3k
Mounîm A. El‐Yacoubi France	20	544 0.4×	336 0.5×	125 0.2×	43 0.1×	53 0.2×	88	1.3k
Taha H. Rassem Malaysia	13	562 0.4×	267 0.4×	102 0.2×	290 0.5×	123 0.5×	40	1.1k
Sajid Ali Khan Pakistan	17	550 0.4×	394 0.6×	144 0.2×	91 0.2×	246 1.0×	27	1.1k
Imran Siddiqi Pakistan	26	1.7k 1.2×	570 0.8×	592 1.0×	30 0.1×	30 0.1×	118	2.2k
Türker Tuncer Türkiye	18	339 0.2×	336 0.5×	43 0.1×	109 0.2×	223 0.9×	89	1.2k
Siqi Liu China	15	255 0.2×	412 0.6×	80 0.1×	255 0.5×	197 0.8×	74	1.1k
Shuihua Wang United Kingdom	20	417 0.3×	502 0.7×	81 0.1×	185 0.3×	385 1.6×	66	1.4k
Sajid Iqbal Pakistan	18	622 0.4×	573 0.8×	43 0.1×	616 1.1×	384 1.6×	48	1.5k

Countries citing papers authored by Saeeda Naz

Since Specialization

Citations

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

Fields of papers citing papers by Saeeda Naz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saeeda Naz

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

Chang, Chunqi, et al.. (2025). Novel deep learning solutions with layered recurrent neural networks for nonlinear stiff Dahl hysteresis model in piezoelectric actuator. Neural Networks. 196. 108378–108378.

Naz, Saeeda, et al.. (2023). A Deep Learning Approach for Diabetic Foot Ulcer Classification and Recognition. Information. 14(1). 36–36. 43 indexed citations

Rehman, Arshia, et al.. (2023). Review on chest pathogies detection systems using deep learning techniques. Artificial Intelligence Review. 56(11). 12607–12653. 10 indexed citations

Razzak, Imran, Saeeda Naz, Abida Ashraf, et al.. (2022). Mutliresolutional ensemble PartialNet for Alzheimer detection using magnetic resonance imaging data. International Journal of Intelligent Systems. 37(10). 6613–6630. 22 indexed citations

Ahmad, Riaz, Saeeda Naz, Muhammad Zeshan Afzal, et al.. (2020). A Deep Learning based Arabic Script Recognition System: Benchmark on KHAT. The International Arab Journal of Information Technology. 17(3). 299–305. 16 indexed citations

Ahmed, Saad Bin, Ibrahim A. Hameed, Saeeda Naz, Imran Razzak, & Rubiyah Yusof. (2019). Evaluation of Handwritten Urdu Text by Integration of MNIST Dataset Learning Experience. IEEE Access. 7. 153566–153578. 12 indexed citations

Naz, Saeeda, Arif Iqbal Umar, Saad Bin Ahmed, et al.. (2018). Statistical features extraction for character recognition using recurrent neural network. Deakin Research Online (Deakin University). 34(1). 47–53. 9 indexed citations

Ahmed, Saad Bin, et al.. (2017). Deep learning based isolated Arabic scene character recognition. 46–51. 41 indexed citations

Ahmed, Saad Bin, Saeeda Naz, Salah Ud Din, et al.. (2017). UCOM offline dataset-an Urdu handwritten dataset generation. The International Arab Journal of Information Technology. 14(2). 239–245. 24 indexed citations

10.

Naz, Saeeda, et al.. (2017). Automated techniques for brain tumor segmentation and detection: A review study. 1–6. 12 indexed citations

11.

Shirazi, Syed Hamad, et al.. (2017). Extreme learning machine based microscopic red blood cells classification. Cluster Computing. 21(1). 691–701. 29 indexed citations

12.

Naz, Saeeda, Arif Iqbal Umar, & Imran Razzak. (2016). Lexicon reduction for Urdu/Arabic script based character recognition: A multilingual OCR. SHILAP Revista de lepidopterología. 3 indexed citations

13.

Naz, Saeeda, Arif Iqbal Umar, Riaz Ahmed, et al.. (2016). Urdu Nasta’liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks. SpringerPlus. 5(1). 2010–2010. 36 indexed citations

14.

Naz, Saeeda, Arif Iqbal Umar, & Imran Razzak. (2015). A hybrid approach for NER system for Scarce Resourced Language-URDU: Integrating n-gram with rules and gazetteers. SHILAP Revista de lepidopterología. 5 indexed citations

15.

Ahmad, Riaz, et al.. (2015). Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach. PLoS ONE. 10(9). e0133648–e0133648. 22 indexed citations

16.

Naz, Saeeda, et al.. (2014). The Optical Character Recognition for Cursive Script Using HMM: A Review. Research Journal of Applied Sciences Engineering and Technology. 8(19). 2016–2025. 4 indexed citations

17.

Naz, Saeeda, et al.. (2014). Learning Programming through Multimedia and Dry-run. Research Journal of Applied Sciences Engineering and Technology. 7(21). 4455–4463. 4 indexed citations

18.

Naz, Saeeda, Arif Iqbal Umar, Syed Hamad Shirazi, et al.. (2014). Challenges of Urdu Named Entity Recognition: A Scarce Resourced Languageq. Research Journal of Applied Sciences Engineering and Technology. 8(10). 1272–1278. 20 indexed citations

19.

Shirazi, Syed Hamad, et al.. (2014). Curvelet Based Offline Analysis of SEM Images. PLoS ONE. 9(8). e103942–e103942. 7 indexed citations

20.

Naz, Saeeda, et al.. (2013). Challenges in baseline detection of cursive script languages. Own your potential (DEAKIN). 551–556. 6 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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