Daniel Tchiotsop
Impact in
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- Chaos control and synchronization
- stochastic dynamics and bifurcation
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
Papers in
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- Blind Source Separation Techniques 11
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- Digital Imaging for Blood Diseases 11
- Co-authors
- Alexis Nguomkam Negou (4 shared papers)Jacques Ndé Kengne (4 shared papers)Didier Wolf (16 shared papers)Hilaire Bertrand Fotsin (5 shared papers)Zeric Tabekoueng Njitacke (1 shared paper)Aurelle Tchagna Kouanou (8 shared papers)Valérie Louis-Dorr (8 shared papers)Réné Tchinda (10 shared papers)
In The Last Decade
Daniel Tchiotsop
49 papers receiving 828 citations
Peers
Comparison fields: 5 of 109
- Statistical and Nonlinear Physics 327
- Cognitive Neuroscience 205
- Computer Networks and Communications 213
- Computer Vision and Pattern Recognition 189
- Health Informatics 11
Countries citing papers authored by Daniel Tchiotsop
This map shows the geographic impact of Daniel Tchiotsop'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 Daniel Tchiotsop with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Tchiotsop more than expected).
Fields of papers citing papers by Daniel Tchiotsop
This network shows the impact of papers produced by Daniel Tchiotsop. 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 Daniel Tchiotsop. The network helps show where Daniel Tchiotsop may publish in the future.
Co-authors
The 21 scholars most cited alongside Daniel Tchiotsop, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 164 | |
| 2 | 2016 | 146 | |
| 3 | 2021 | 73 | |
| 4 | 2021 | 53 | |
| 5 | 2018 | 51 | |
| 6 | 2020 | 38 | |
| 7 | 2019 | 27 | |
| 8 | 2021 | 26 | |
| 9 | 2021 | 21 | |
| 10 | 2020 | 21 | |
| 11 | 2007 | 18 | |
| 12 | 2018 | 18 | |
| 13 | 2020 | 17 | |
| 14 | 2018 | 17 | |
| 15 | 2018 | 16 | |
| 16 | 2015 | 13 | |
| 17 | 2021 | 13 | |
| 18 | 2019 | 12 | |
| 19 | 2015 | 11 | |
| 20 | 2020 | 11 |
About Daniel Tchiotsop
Daniel Tchiotsop is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Artificial Intelligence, having authored 50 papers that have together received 856 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (11 papers), Blind Source Separation Techniques (11 papers), EEG and Brain-Computer Interfaces (10 papers), ECG Monitoring and Analysis (9 papers), AI in cancer detection (7 papers), Neural Networks and Applications (6 papers), COVID-19 diagnosis using AI (5 papers) and Image Processing Techniques and Applications (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (327 citations), Cognitive Neuroscience (205 citations), Computer Networks and Communications (213 citations), Computer Vision and Pattern Recognition (189 citations) and Health Informatics (11 citations). Daniel Tchiotsop has collaborated with scholars based in Cameroon, France and Rwanda. Frequent co-authors include Alexis Nguomkam Negou, Jacques Ndé Kengne, Didier Wolf, Hilaire Bertrand Fotsin, Zeric Tabekoueng Njitacke, Aurelle Tchagna Kouanou, Valérie Louis-Dorr, Réné Tchinda, Michel Noubom and Godpromesse Kenné. Their work appears in journals such as Chaos Solitons & Fractals, Heliyon, Informatics in Medicine Unlocked, Multimedia Tools and Applications and Physical and Engineering Sciences in Medicine.
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.