Umme Sara

1.7k total citations · 1 hit paper
8 papers, 1.0k citations indexed

About

Umme Sara is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Umme Sara has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Health Information Management. Recurrent topics in Umme Sara's work include Artificial Intelligence in Healthcare (2 papers), Spam and Phishing Detection (1 paper) and Advanced Image Fusion Techniques (1 paper). Umme Sara is often cited by papers focused on Artificial Intelligence in Healthcare (2 papers), Spam and Phishing Detection (1 paper) and Advanced Image Fusion Techniques (1 paper). Umme Sara collaborates with scholars based in Bangladesh. Umme Sara's co-authors include Mohammad Shorif Uddin, Morium Akter, Aditya Rajbongshi, Anichur Rahman, Saiful Islam, Diganta Bhusan Das, Dipanjali Kundu and Abu Bakkar Siddik and has published in prestigious journals such as Data in Brief, International Journal of Advanced Computer Science and Applications and International Journal of Advanced Technology and Engineering Exploration.

In The Last Decade

Umme Sara

7 papers receiving 994 citations

Hit Papers

Image Quality Assessment through FSIM, SSIM, MSE and PSNR... 2019 2026 2021 2023 2019 250 500 750
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.

  1. Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study
    2019 943 citations Umme Sara, Morium Akter et al. Journal of Computer and Communications profile →

Peers

Umme Sara
Morium Akter Bangladesh
Wenxian Zheng China
Zhanjie Song China
Ayush Dogra India
Sei‐ichiro Kamata Japan
Long Xu China
Zhihao Wang China
L. Ganesan India
Kun Zeng China
Zhenghua Huang China
Morium Akter Bangladesh
Umme Sara
Citations per year, relative to Umme Sara Umme Sara (= 1×) peers Morium Akter

Countries citing papers authored by Umme Sara

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

8 of 8 papers shown
1.
Sara, Umme, et al.. (2025). Automated Skin Cancer Classification and Detection Using Convolutional Neural Networks and Dermoscopy Images. Procedia Computer Science. 252. 108–117. 1 indexed citations
2.
3.
Rajbongshi, Aditya, et al.. (2022). A comprehensive guava leaves and fruits dataset for guava disease recognition. Data in Brief. 42. 108174–108174. 26 indexed citations
4.
Rajbongshi, Aditya, et al.. (2022). Utilization of Five-Distinct Dataset to Diagnose and Predict Heart Disease: A Machine Learning Approach. 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT). 1–6. 4 indexed citations
5.
Rajbongshi, Aditya, et al.. (2022). A Machine Learning Approach to Detect the Brain Stroke Disease. 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT). 897–901. 31 indexed citations
6.
Islam, Saiful, et al.. (2021). SGBBA: An Efficient Method for Prediction System in Machine Learning using Imbalance Dataset. International Journal of Advanced Computer Science and Applications. 12(3). 25 indexed citations
7.
Sara, Umme, Morium Akter, & Mohammad Shorif Uddin. (2019). Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study. Journal of Computer and Communications. 7(3). 8–18. 943 indexed citations breakdown →
8.
Siddik, Abu Bakkar, et al.. (2019). Towards the development of an energy-efficient smart home through IoT. International Journal of Advanced Technology and Engineering Exploration. 6(58). 208–216. 5 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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2026