Umme Sara
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 2%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Mohammad Shorif UddinMorium AkterAditya RajbongshiAnichur RahmanSaiful IslamDiganta Bhusan DasDipanjali KunduAbu Bakkar Siddik
- Topics
- Artificial Intelligence in Healthcare (2 papers)Spam and Phishing Detection (1 paper)Advanced Image Fusion Techniques (1 paper)
- Journals
- Data in BriefInternational Journal of Advanced Computer Science and ApplicationsInternational Journal of Advanced Technology and Engineering Exploration
- Partner nations
- Bangladesh
In The Last Decade
Umme Sara
7 papers receiving 994 citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Computer Vision and Pattern Recognition 544
- Media Technology 211
- Artificial Intelligence 144
- Biomedical Engineering 141
- Radiology, Nuclear Medicine and Imaging 135
Countries citing papers authored by Umme Sara
This map shows the geographic impact of Umme Sara'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 Umme Sara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Umme Sara more than expected).
Fields of papers citing papers by Umme Sara
This network shows the impact of papers produced by Umme Sara. 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 Umme Sara. The network helps show where Umme Sara may publish in the future.
Co-authorship network of co-authors of Umme Sara
This figure shows the co-authorship network connecting the top 25 collaborators of Umme Sara. A scholar is included among the top collaborators of Umme Sara 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 Umme Sara. Umme Sara 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 | 26 | |
| 4 | 4 | |
| 5 | 31 | |
| 6 | 25 | |
| 7 | Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Studybreakdown → | 943 |
| 8 | 5 |
About Umme Sara
Umme Sara is a scholar working on Medical Laboratory Technology, Health Information Management and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 1.0k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (2 papers), Spam and Phishing Detection (1 paper) and Advanced Image Fusion Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (544 citations), Media Technology (211 citations) and Acoustics and Ultrasonics (20 citations). Umme Sara has collaborated with scholars based in Bangladesh. Frequent co-authors include Mohammad Shorif Uddin, Morium Akter, Aditya Rajbongshi, Anichur Rahman, Saiful Islam, Diganta Bhusan Das, Dipanjali Kundu and Abu Bakkar Siddik. Their work appears in journals such as Data in Brief, International Journal of Advanced Computer Science and Applications and International Journal of Advanced Technology and Engineering Exploration.
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.