Arvind Dhaka
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Image and Signal Denoising Methods
- Image Enhancement Techniques
Papers in
- Neurology 16
- Brain Tumor Detection and Classification 16
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- Advanced Steganography and Watermarking Techniques 7
- Chaos-based Image/Signal Encryption 5
- Digital Imaging for Blood Diseases 4
- Co-authors
- Amita Nandal (37 shared papers)Arpit Kumar Sharma (16 shared papers)Kemal Polat (5 shared papers)Adi Alhudhaif (5 shared papers)Fayadh S. Alenezi (3 shared papers)Hamurabi Gamboa-Rosales (9 shared papers)Liang Dao Zhou (1 shared paper)Rahul Dixit (3 shared papers)
- Journals
- Scientific Reports (7 papers)Wireless Personal Communications (4 papers)IEEE Access (4 papers)Biomedical Signal Processing and Control (3 papers)Symmetry (2 papers)
- Partner nations
- IndiaChinaBangladesh
In The Last Decade
Arvind Dhaka
47 papers receiving 468 citations
Peers
Comparison fields: 5 of 79
- Neurology 141
- Computer Vision and Pattern Recognition 188
- Media Technology 41
- Modeling and Simulation 20
- Artificial Intelligence 102
Countries citing papers authored by Arvind Dhaka
This map shows the geographic impact of Arvind Dhaka'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 Arvind Dhaka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arvind Dhaka more than expected).
Fields of papers citing papers by Arvind Dhaka
This network shows the impact of papers produced by Arvind Dhaka. 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 Arvind Dhaka. The network helps show where Arvind Dhaka may publish in the future.
Co-authors
The 25 scholars most cited alongside Arvind Dhaka, 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 62 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 89 | |
| 2 | 2018 | 57 | |
| 3 | 2023 | 54 | |
| 4 | 2015 | 34 | |
| 5 | 2021 | 25 | |
| 6 | 2018 | 17 | |
| 7 | 2020 | 17 | |
| 8 | 2023 | 16 | |
| 9 | 2024 | 16 | |
| 10 | 2022 | 13 | |
| 11 | 2025 | 12 | |
| 12 | 2015 | 10 | |
| 13 | 2023 | 10 | |
| 14 | 2021 | 9 | |
| 15 | 2025 | 9 | |
| 16 | 2021 | 9 | |
| 17 | 2021 | 8 | |
| 18 | 2021 | 8 | |
| 19 | 2022 | 6 | |
| 20 | 2018 | 6 |
About Arvind Dhaka
Arvind Dhaka is a scholar working on Neurology, Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 62 papers that have together received 487 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (16 papers), AI in cancer detection (11 papers), Advanced MIMO Systems Optimization (8 papers), Advanced Steganography and Watermarking Techniques (7 papers), Advanced Image Fusion Techniques (6 papers), Advanced Wireless Communication Techniques (6 papers), Chaos-based Image/Signal Encryption (5 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Neurology (141 citations), Computer Vision and Pattern Recognition (188 citations), Media Technology (41 citations), Modeling and Simulation (20 citations) and Artificial Intelligence (102 citations). Arvind Dhaka has collaborated with scholars based in India, China and Bangladesh. Frequent co-authors include Amita Nandal, Arpit Kumar Sharma, Kemal Polat, Adi Alhudhaif, Fayadh S. Alenezi, Hamurabi Gamboa-Rosales, Liang Dao Zhou, Rahul Dixit, Carlos Eric Galvan-Tejada and Jose-Maria Celaya-Padilla. Their work appears in journals such as Scientific Reports, Wireless Personal Communications, IEEE Access, Biomedical Signal Processing and Control and Symmetry.
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.