Fuseini Mumuni
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- Advanced Vision and Imaging 4
- Optical measurement and interference techniques 2
- Advanced Neural Network Applications 2
- Face recognition and analysis 1
- Artificial Intelligence top 10%
- Machine Learning and Data Classification 2
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- Robotics and Sensor-Based Localization 4
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- Advanced Control Systems Optimization 1
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- Computer Graphics and Visualization Techniques 1
- Co-authors
- Alhassan Mumuni
- Journals
- SHILAP Revista de lepidopterología (2 papers)Knowledge and Information Systems (1 paper)Cognitive Systems Research (1 paper)
In The Last Decade
Fuseini Mumuni
11 papers receiving 495 citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Computer Vision and Pattern Recognition 131
- Health Informatics 8
- Artificial Intelligence 137
- Industrial and Manufacturing Engineering 37
- Health Information Management 14
Countries citing papers authored by Fuseini Mumuni
This map shows the geographic impact of Fuseini Mumuni'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 Fuseini Mumuni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fuseini Mumuni more than expected).
Fields of papers citing papers by Fuseini Mumuni
This network shows the impact of papers produced by Fuseini Mumuni. 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 Fuseini Mumuni. The network helps show where Fuseini Mumuni may publish in the future.
Co-authorship network
The 1 scholars most cited alongside Fuseini Mumuni, 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 | 2025 | 5 | |
| 2 | 2024 | 4 | |
| 3 | Automated data processing and feature engineering for deep learning and big data applications: A surveybreakdown → | 2024 | 55 |
| 4 | 2023 | 12 | |
| 5 | 2022 | 9 | |
| 6 | 2022 | 8 | |
| 7 | 2022 | 4 | |
| 8 | Data augmentation: A comprehensive survey of modern approachesbreakdown → | 2022 | 382 |
| 9 | 2022 | 1 | |
| 10 | 2021 | 15 | |
| 11 | 2021 | 40 | |
| 12 | Development of a State-Space Thermal Model for High Precision Temperature Control of a Poultry Incubator | 2015 | 0 |
About Fuseini Mumuni
Fuseini Mumuni is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Aerospace Engineering, having authored 12 papers that have together received 535 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (4 papers), Robotics and Sensor-Based Localization (4 papers), Optical measurement and interference techniques (2 papers), Advanced Neural Network Applications (2 papers), Machine Learning and Data Classification (2 papers), Advanced Control Systems Optimization (1 paper), Face recognition and analysis (1 paper) and Computer Graphics and Visualization Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (131 citations), Health Informatics (8 citations) and Artificial Intelligence (137 citations). Fuseini Mumuni has collaborated with scholars based in Ghana and Malaysia. Frequent co-authors include Alhassan Mumuni. Their work appears in journals such as SHILAP Revista de lepidopterología, Knowledge and Information Systems and Cognitive Systems Research.
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.