Jafar Tanha

1.4k total citations
76 papers, 841 citations indexed

About

Jafar Tanha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Jafar Tanha has authored 76 papers receiving a total of 841 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Artificial Intelligence, 23 papers in Computer Vision and Pattern Recognition and 9 papers in Computer Networks and Communications. Recurrent topics in Jafar Tanha's work include Anomaly Detection Techniques and Applications (16 papers), Text and Document Classification Technologies (12 papers) and Machine Learning and Data Classification (9 papers). Jafar Tanha is often cited by papers focused on Anomaly Detection Techniques and Applications (16 papers), Text and Document Classification Technologies (12 papers) and Machine Learning and Data Classification (9 papers). Jafar Tanha collaborates with scholars based in Iran, Netherlands and United States. Jafar Tanha's co-authors include Maarten van Someren, Hamideh Afsarmanesh, Negin Samadi, Yousef Abdi, Mohammad Asadpour, Mohammad Ali Balafar, Amin Golzari Oskouei, Arash Sharifi, Ali Ahmadi and Mehdi Hosseinzadeh Aghdam and has published in prestigious journals such as IEEE Access, Pattern Recognition and Information Sciences.

In The Last Decade

Jafar Tanha

65 papers receiving 812 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jafar Tanha Iran 13 512 178 93 79 59 76 841
Zhenyun Deng China 8 312 0.6× 139 0.8× 90 1.0× 74 0.9× 57 1.0× 17 707
Matthias Feurer Germany 6 651 1.3× 128 0.7× 92 1.0× 66 0.8× 55 0.9× 9 1.0k
Qingchen Zhang China 3 327 0.6× 152 0.9× 91 1.0× 122 1.5× 91 1.5× 5 816
Aaron Klein Germany 8 753 1.5× 236 1.3× 84 0.9× 71 0.9× 92 1.6× 25 1.2k
Jwan Najeeb Saeed Iraq 12 331 0.6× 231 1.3× 61 0.7× 78 1.0× 61 1.0× 17 855
Dharmender Kumar India 14 269 0.5× 100 0.6× 94 1.0× 109 1.4× 48 0.8× 66 832
Rafael M. O. Cruz Canada 15 840 1.6× 272 1.5× 143 1.5× 56 0.7× 104 1.8× 52 1.2k
Chung-Chian Hsu Taiwan 16 411 0.8× 140 0.8× 115 1.2× 43 0.5× 46 0.8× 52 743
Abu Sarwar Zamani Saudi Arabia 17 279 0.5× 153 0.9× 100 1.1× 130 1.6× 82 1.4× 90 862
Bin Qian China 7 327 0.6× 95 0.5× 80 0.9× 121 1.5× 51 0.9× 15 725

Countries citing papers authored by Jafar Tanha

Since Specialization
Citations

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

Fields of papers citing papers by Jafar Tanha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jafar Tanha

This figure shows the co-authorship network connecting the top 25 collaborators of Jafar Tanha. A scholar is included among the top collaborators of Jafar Tanha 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 Jafar Tanha. Jafar Tanha 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.
Tanha, Jafar, et al.. (2025). A Novel Multimodal Deep Learning Approach With Loss Function for Detection of Sleep Apnea Events. IEEE Access. 13. 52085–52099. 1 indexed citations
2.
Tanha, Jafar, et al.. (2025). Self-adaptive over and under-sampling approach based on boosting with a new weighting factor for imbalanced data classification. Computers & Electrical Engineering. 129. 110783–110783.
3.
Mohammad‐Alizadeh‐Charandabi, Sakineh, et al.. (2025). Developing and validating an artificial intelligence-based application for predicting some pregnancy outcomes: a multi-phase study protocol. Reproductive Health. 22(1). 99–99.
4.
Tanha, Jafar, et al.. (2024). A deep ensemble medical image segmentation with novel sampling method and loss function. Computers in Biology and Medicine. 172. 108305–108305. 13 indexed citations
5.
Samadi, Negin, Jafar Tanha, & Mahdi Jalili. (2024). Graph theory-based semi-supervised self-training for data stream classification and emerging class detection. Information Sciences. 698. 121762–121762.
6.
Oskouei, Amin Golzari, Negin Samadi, Jafar Tanha, & Asgarali Bouyer. (2024). SSFCM-FWCW: Semi-Supervised Fuzzy C-Means method based on Feature-Weight and Cluster-Weight learning. Software Impacts. 21. 100678–100678. 9 indexed citations
7.
Khanli, Leyli Mohammad, et al.. (2024). A Fast Multi-Network K-Dependence Bayesian Classifier for Continuous Features. Pattern Recognition. 150. 110299–110299.
8.
Pashazadeh, Saeid, et al.. (2024). Modeling Chandy–Lamport Distributed Snapshot Algorithm Using Colored Petri Net. IET Software. 2024(1). 1 indexed citations
9.
Tanha, Jafar, et al.. (2024). A novel deep learning model based on transformer and cross modality attention for classification of sleep stages. Journal of Biomedical Informatics. 157. 104689–104689. 9 indexed citations
10.
Tanha, Jafar, et al.. (2024). Neighborhood information based semi-supervised fuzzy C-means employing feature-weight and cluster-weight learning. Chaos Solitons & Fractals. 181. 114670–114670. 10 indexed citations
11.
Tanha, Jafar, et al.. (2024). An experimental review of the ensemble-based data stream classification algorithms in non-stationary environments. Computers & Electrical Engineering. 118. 109420–109420. 1 indexed citations
12.
Tanha, Jafar, et al.. (2024). Lung Cancer classification using an ensemble of CNNs Method in CT Scan Images. 14(2). 1 indexed citations
13.
Oskouei, Amin Golzari, Negin Samadi, Jafar Tanha, Asgarali Bouyer, & Bahman Arasteh. (2024). Viewpoint‐Based Collaborative Feature‐Weighted Multi‐View Intuitionistic Fuzzy Clustering Using Neighborhood Information. Neurocomputing. 617. 128884–128884. 5 indexed citations
14.
Samadi, Negin, Jafar Tanha, & Mahdi Jalili. (2024). A Weighted Semi-supervised Possibilistic Fuzzy c-Means algorithm for data stream classification and emerging class detection. Knowledge-Based Systems. 309. 112831–112831. 3 indexed citations
15.
Tanha, Jafar, et al.. (2022). Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method. Computers in Biology and Medicine. 151(Pt A). 106276–106276. 6 indexed citations
16.
Tanha, Jafar, et al.. (2021). A hybrid semi-supervised boosting to sentiment analysis. International journal of nonlinear analysis and applications. 12(2). 1769–1784. 1 indexed citations
17.
Mohseni, Mahsa & Jafar Tanha. (2021). A Density-based Undersampling Approach to Intrusion Detection. 1–7. 2 indexed citations
18.
Tanha, Jafar, et al.. (2020). A predictive model based on machine learning methods to recognize fake Persian news on twitter. International journal of nonlinear analysis and applications. 11. 119–128. 1 indexed citations
19.
Tanha, Jafar, et al.. (2015). Combining higher-order N-grams and intelligent sample selection to improve language modeling for Handwritten Text Recognition.. The European Symposium on Artificial Neural Networks. 1 indexed citations
20.
Tanha, Jafar, et al.. (2011). Providing a comprehensive knowledge management model. 1(6). 155–163. 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Zhenyun Deng Breakdown of academic impact, for papers by Matthias Feurer Breakdown of academic impact, for papers by Qingchen Zhang Breakdown of academic impact, for papers by Aaron Klein Breakdown of academic impact, for papers by Jwan Najeeb Saeed Breakdown of academic impact, for papers by Dharmender Kumar Breakdown of academic impact, for papers by Rafael M. O. Cruz Breakdown of academic impact, for papers by Chung-Chian Hsu Breakdown of academic impact, for papers by Abu Sarwar Zamani Breakdown of academic impact, for papers by Bin Qian
Rankless by CCL
2026