Arvind Dhaka
Impact in
- Neurology top 5%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Image and Signal Denoising Methods
- Image Enhancement Techniques
Papers in
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- Advanced Steganography and Watermarking Techniques 5
- Chaos-based Image/Signal Encryption 5
- Digital Imaging for Blood Diseases 4
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- AI in cancer detection 10
- Co-authors
- Amita Nandal (28 shared papers)Arpit Kumar Sharma (9 shared papers)Kemal Polat (5 shared papers)Adi Alhudhaif (5 shared papers)Fayadh Alenezi (3 shared papers)Hamurabi Gamboa-Rosales (9 shared papers)Liang Zhou (1 shared paper)Jorge I. Galván-Tejada (2 shared papers)
- Journals
- IEEE Access (4 papers)Wireless Personal Communications (4 papers)Scientific Reports (4 papers)Biomedical Signal Processing and Control (3 papers)Wireless Communications and Mobile Computing (2 papers)
- Partner nations
- IndiaChinaUnited States
In The Last Decade
Arvind Dhaka
40 papers receiving 393 citations
Peers
Comparison fields: 5 of 78
- Neurology 128
- Computer Vision and Pattern Recognition 173
- Media Technology 40
- Modeling and Simulation 18
- Artificial Intelligence 90
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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 76 | |
| 2 | 2018 | 55 | |
| 3 | 2023 | 47 | |
| 4 | 2015 | 31 | |
| 5 | 2021 | 23 | |
| 6 | 2018 | 15 | |
| 7 | 2023 | 14 | |
| 8 | 2020 | 14 | |
| 9 | 2024 | 13 | |
| 10 | 2022 | 12 | |
| 11 | 2021 | 9 | |
| 12 | 2021 | 8 | |
| 13 | 2015 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2021 | 7 | |
| 16 | 2021 | 7 | |
| 17 | 2018 | 6 | |
| 18 | 2025 | 6 | |
| 19 | 2021 | 6 | |
| 20 | 2022 | 5 |
About Arvind Dhaka
Arvind Dhaka is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology, Electrical and Electronic Engineering and Media Technology, having authored 49 papers that have together received 410 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (14 papers), AI in cancer detection (10 papers), Advanced MIMO Systems Optimization (7 papers), Advanced Image Fusion Techniques (6 papers), Advanced Wireless Communication Techniques (6 papers), Advanced Steganography and Watermarking Techniques (5 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 (128 citations), Computer Vision and Pattern Recognition (173 citations), Media Technology (40 citations), Modeling and Simulation (18 citations) and Artificial Intelligence (90 citations). Arvind Dhaka has collaborated with scholars based in India, China and United States. Frequent co-authors include Amita Nandal, Arpit Kumar Sharma, Kemal Polat, Adi Alhudhaif, Fayadh Alenezi, Hamurabi Gamboa-Rosales, Liang Zhou, Jorge I. Galván-Tejada, José M. Celaya-Padilla and Carlos E. Galván-Tejada. Their work appears in journals such as IEEE Access, Wireless Personal Communications, Scientific Reports, Biomedical Signal Processing and Control and Wireless Communications and Mobile Computing.
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.