Md. Eshmam Rayed
Impact in
-
- Brain Tumor Detection and Classification
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 1
- COVID-19 diagnosis using AI 1
-
- Smart Agriculture and AI 2
- Phytoplasmas and Hemiptera pathogens 1
- Leaf Properties and Growth Measurement 1
Md. Eshmam Rayed
5 papers receiving 185 citations
Md. Eshmam Rayed's Hit Papers
Peers
Comparison fields: 5 of 60
- Health Informatics 7
- Neurology 28
- Computer Vision and Pattern Recognition 48
- Radiology, Nuclear Medicine and Imaging 44
- Industrial and Manufacturing Engineering 15
Countries citing papers authored by Md. Eshmam Rayed
This map shows the geographic impact of Md. Eshmam Rayed'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 Md. Eshmam Rayed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Md. Eshmam Rayed more than expected).
Fields of papers citing papers by Md. Eshmam Rayed
This network shows the impact of papers produced by Md. Eshmam Rayed. 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 Md. Eshmam Rayed. The network helps show where Md. Eshmam Rayed may publish in the future.
Co-authors
The 7 scholars most cited alongside Md. Eshmam Rayed, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Deep learning for medical image segmentation: State-of-the-art advancements and challenges Hit paper breakdown → | 2024 | 137 |
| 2 | 2024 | 46 | |
| 3 | 2025 | 4 | |
| 4 | 2025 | 3 | |
| 5 | 2023 | 1 |
About Md. Eshmam Rayed
Md. Eshmam Rayed is a scholar working on Radiology, Nuclear Medicine and Imaging, Plant Science, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 5 papers that have together received 191 indexed citations. Recurring topics across this work include Smart Agriculture and AI (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Phytoplasmas and Hemiptera pathogens (1 paper), Leaf Properties and Growth Measurement (1 paper), Advanced Neural Network Applications (1 paper), COVID-19 diagnosis using AI (1 paper), Manufacturing Process and Optimization (1 paper) and Brain Tumor Detection and Classification (1 paper). The work is most often cited by research in Health Informatics (7 citations), Neurology (28 citations), Computer Vision and Pattern Recognition (48 citations), Radiology, Nuclear Medicine and Imaging (44 citations) and Industrial and Manufacturing Engineering (15 citations). Md. Eshmam Rayed has collaborated with scholars based in Bangladesh, Malaysia and Japan. Frequent co-authors include M. F. Mridha, Md. Mohsin Kabir, Jamin Rahman Jim, Satoshi Nishimura, Jungpil Shin, Md. Jakir Hossen and Kamruddin Nur. Their work appears in journals such as IEEE Access, PLoS ONE and Informatics in Medicine Unlocked.
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.