Godwin Brown Tunze
- Artificial Intelligence top 10%
- Aerospace Engineering
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Co-authors
- Jae‐Min LeeDong‐Seong KimMounir HamdiThien Huynh‐TheM. PoongodiSarita SimaiyaV. VijayakumarAmandeep Kaur
- Topics
- Wireless Signal Modulation Classification (3 papers)Artificial Intelligence in Healthcare (2 papers)Complex Network Analysis Techniques (2 papers)
- Journals
- IEEE Transactions on Vehicular TechnologyComputational and Mathematical Methods in MedicineInternational Journal of Information Technology and Web Engineering
In The Last Decade
Godwin Brown Tunze
8 papers receiving 281 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 139
- Aerospace Engineering 49
- Information Systems 47
- Computer Vision and Pattern Recognition 42
- Computer Networks and Communications 34
Countries citing papers authored by Godwin Brown Tunze
This map shows the geographic impact of Godwin Brown Tunze'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 Godwin Brown Tunze with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Godwin Brown Tunze more than expected).
Fields of papers citing papers by Godwin Brown Tunze
This network shows the impact of papers produced by Godwin Brown Tunze. 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 Godwin Brown Tunze. The network helps show where Godwin Brown Tunze may publish in the future.
Co-authorship network of co-authors of Godwin Brown Tunze
This figure shows the co-authorship network connecting the top 25 collaborators of Godwin Brown Tunze. A scholar is included among the top collaborators of Godwin Brown Tunze 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 Godwin Brown Tunze. Godwin Brown Tunze is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 23 | |
| 3 | 17 | |
| 4 | Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniquesbreakdown → | 124 |
| 5 | 21 | |
| 6 | 3 | |
| 7 | 26 | |
| 8 | 72 |
About Godwin Brown Tunze
Godwin Brown Tunze is a scholar working on Health Information Management, Computer Science Applications and Statistical and Nonlinear Physics, having authored 8 papers that have together received 294 indexed citations. Recurring topics across this work include Wireless Signal Modulation Classification (3 papers), Artificial Intelligence in Healthcare (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (139 citations), Health Information Management (12 citations) and Health Informatics (3 citations). Godwin Brown Tunze has collaborated with scholars based in Tanzania, India and Qatar. Frequent co-authors include Jae‐Min Lee, Dong‐Seong Kim, Mounir Hamdi, Thien Huynh‐The, M. Poongodi, Sarita Simaiya, V. Vijayakumar, Amandeep Kaur, Abeer D. Algarni and Umesh Kumar Lilhore. Their work appears in journals such as IEEE Transactions on Vehicular Technology, Computational and Mathematical Methods in Medicine and International Journal of Information Technology and Web Engineering.
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.