Jafar Tanha
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Co-authors
- Maarten van SomerenHamideh AfsarmaneshNegin SamadiYousef AbdiMohammad AsadpourMohammad Ali BalafarAmin Golzari OskoueiArash Sharifi
- Topics
- Anomaly Detection Techniques and Applications (16 papers)Text and Document Classification Technologies (12 papers)Machine Learning and Data Classification (9 papers)
- Cited by
- Artificial IntelligenceHealth Information ManagementComputer Vision and Pattern Recognition
- Partner nations
- IranNetherlandsUnited States
In The Last Decade
Jafar Tanha
65 papers receiving 812 citations
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 512
- Computer Vision and Pattern Recognition 178
- Information Systems 93
- Computer Networks and Communications 79
- Electrical and Electronic Engineering 59
Countries citing papers authored by Jafar Tanha
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 13 | |
| 5 | 0 | |
| 6 | 9 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 9 | |
| 10 | 10 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 5 | |
| 14 | 3 | |
| 15 | 6 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | Combining higher-order N-grams and intelligent sample selection to improve language modeling for Handwritten Text Recognition. | 1 |
| 20 | Providing a comprehensive knowledge management model | 2 |
About Jafar Tanha
Jafar Tanha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology, having authored 76 papers that have together received 841 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (16 papers), Text and Document Classification Technologies (12 papers) and Machine Learning and Data Classification (9 papers). The work is most often cited by research in Artificial Intelligence (512 citations), Health Information Management (55 citations) and Computer Vision and Pattern Recognition (178 citations). Jafar Tanha has collaborated with scholars based in Iran, Netherlands and United States. Frequent 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. Their work appears in journals such as IEEE Access, Pattern Recognition and Information Sciences.
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.