Younes Akbari

851 total citations
44 papers, 449 citations indexed

About

Younes Akbari is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Younes Akbari has authored 44 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 8 papers in Media Technology. Recurrent topics in Younes Akbari's work include Handwritten Text Recognition Techniques (15 papers), Digital Media Forensic Detection (12 papers) and AI in cancer detection (9 papers). Younes Akbari is often cited by papers focused on Handwritten Text Recognition Techniques (15 papers), Digital Media Forensic Detection (12 papers) and AI in cancer detection (9 papers). Younes Akbari collaborates with scholars based in Qatar, United Arab Emirates and Iran. Younes Akbari's co-authors include Somaya Al-Máadeed, Omar Elharrouss, Noor Almaadeed, Javad Sadri, Imran Siddiqi, Moutaz Saleh, Chawki Djeddi, Kazem Nouri, Ahmed Bouridane and Fouad Khelifi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Younes Akbari

41 papers receiving 429 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Younes Akbari Qatar 13 291 110 74 47 32 44 449
Tabassam Nawaz Pakistan 11 251 0.9× 93 0.8× 91 1.2× 25 0.5× 7 0.2× 18 429
Mohammad Faidzul Nasrudin Malaysia 12 244 0.8× 133 1.2× 61 0.8× 19 0.4× 28 0.9× 60 426
Priyadarsan Parida India 12 159 0.5× 81 0.7× 67 0.9× 12 0.3× 31 1.0× 49 362
A F M Saifuddin Saif Bangladesh 10 207 0.7× 66 0.6× 25 0.3× 33 0.7× 6 0.2× 54 327
Wahab Khan China 13 203 0.7× 73 0.7× 31 0.4× 77 1.6× 41 1.3× 20 542
Abhishek Thakur India 10 118 0.4× 50 0.5× 32 0.4× 31 0.7× 16 0.5× 63 344
Sugandha Agarwal United Arab Emirates 6 557 1.9× 134 1.2× 126 1.7× 13 0.3× 15 0.5× 24 707
Zhuoyao Zhong China 10 489 1.7× 121 1.1× 245 3.3× 26 0.6× 21 0.7× 18 622
Haibing Ren China 12 371 1.3× 113 1.0× 22 0.3× 31 0.7× 36 1.1× 29 457
Nor Azman Ismail Malaysia 10 175 0.6× 95 0.9× 28 0.4× 36 0.8× 37 1.2× 54 418

Countries citing papers authored by Younes Akbari

Since Specialization
Citations

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

Fields of papers citing papers by Younes Akbari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Younes Akbari

This figure shows the co-authorship network connecting the top 25 collaborators of Younes Akbari. A scholar is included among the top collaborators of Younes Akbari 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 Younes Akbari. Younes Akbari 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.
Akbari, Younes, et al.. (2025). Dynamic model scaling based on segmented tumor size for breast cancer detection. Biomedical Signal Processing and Control. 113. 109118–109118.
2.
Kunhoth, Jayakanth, Moutaz Saleh, Somaya Al-Máadeed, Peter Drotár, & Younes Akbari. (2025). Grading of Developmental Dysgraphia Severity in Children: Multimodal Dataset and Classifier Fusion. IEEE Transactions on Cognitive and Developmental Systems. 1–15.
3.
Saleh, Moutaz, et al.. (2025). A review of explainable AI techniques and their evaluation in mammography for breast cancer screening. Clinical Imaging. 123. 110492–110492. 8 indexed citations
4.
Akbari, Younes, et al.. (2025). A novel virtual patient approach for cross-patient multimodal fusion in enhanced breast cancer detection. Computerized Medical Imaging and Graphics. 127. 102687–102687.
5.
Akbari, Younes, et al.. (2025). Breast cancer detection based on histological images using fusion of diffusion model outputs. Scientific Reports. 15(1). 21463–21463. 2 indexed citations
6.
Akbari, Younes, et al.. (2024). Towards improved breast cancer detection via multi-modal fusion and dimensionality adjustment. 1. 100019–100019. 4 indexed citations
7.
Kunhoth, Jayakanth, et al.. (2024). Automated systems for diagnosis of dysgraphia in children: a survey and novel framework. International Journal on Document Analysis and Recognition (IJDAR). 27(4). 707–735. 12 indexed citations
8.
Elharrouss, Omar, et al.. (2024). Backbones-review: Feature extractor networks for deep learning and deep reinforcement learning approaches in computer vision. Computer Science Review. 53. 100645–100645. 31 indexed citations
9.
Akbari, Younes, et al.. (2024). Histopathology in focus: a review on explainable multi-modal approaches for breast cancer diagnosis. Frontiers in Medicine. 11. 1450103–1450103. 18 indexed citations
10.
11.
Akbari, Younes, et al.. (2024). MSEUnet: Refined Intima-media segmentation of the carotid artery based on a multi-scale approach using patch-wise dice loss. Biomedical Signal Processing and Control. 100. 107077–107077. 1 indexed citations
12.
Akbari, Younes, et al.. (2023). A New Framework for Smart Doors Using mmWave Radar and Camera-Based Face Detection and Recognition Techniques. Sensors. 24(1). 172–172. 1 indexed citations
13.
Kunhoth, Jayakanth, Somaya Al-Máadeed, Moutaz Saleh, & Younes Akbari. (2023). CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children. Expert Systems with Applications. 231. 120740–120740. 16 indexed citations
14.
Al-Máadeed, Somaya, et al.. (2022). Hierarchical Fusion Using Subsets of Multi-Features for Historical Arabic Manuscript Dating. Journal of Imaging. 8(3). 60–60. 5 indexed citations
15.
Akbari, Younes, et al.. (2021). Script independent offline writer identification from handwriting samples based on texture using wavelet transform in Persian-English languages. SHILAP Revista de lepidopterología. 18(63). 1–13. 1 indexed citations
16.
Akbari, Younes, Noor Almaadeed, Somaya Al-Máadeed, & Omar Elharrouss. (2021). Applications, databases and open computer vision research from drone videos and images: a survey. Artificial Intelligence Review. 54(5). 3887–3938. 70 indexed citations
17.
Akbari, Younes, et al.. (2020). Binarization of Degraded Document Images Using Convolutional Neural Networks and Wavelet-Based Multichannel Images. IEEE Access. 8. 153517–153534. 17 indexed citations
18.
Akbari, Younes, et al.. (2019). Patch-based offline signature verification using one-class hierarchical deep learning. International Journal on Document Analysis and Recognition (IJDAR). 22(4). 375–385. 21 indexed citations
19.
Akbari, Younes, Kazem Nouri, Javad Sadri, Chawki Djeddi, & Imran Siddiqi. (2016). Wavelet-based gender detection on off-line handwritten documents using probabilistic finite state automata. Image and Vision Computing. 59. 17–30. 45 indexed citations
20.
Sadri, Javad, et al.. (2011). A New System for Recognition of Handwritten Persian Bank Checks. 3. 925–930. 8 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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