Arvind Dhaka

750 total citations
48 papers, 375 citations indexed

About

Arvind Dhaka is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Arvind Dhaka has authored 48 papers receiving a total of 375 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 14 papers in Neurology. Recurrent topics in Arvind Dhaka's work include Brain Tumor Detection and Classification (14 papers), AI in cancer detection (10 papers) and Advanced MIMO Systems Optimization (7 papers). Arvind Dhaka is often cited by papers focused on Brain Tumor Detection and Classification (14 papers), AI in cancer detection (10 papers) and Advanced MIMO Systems Optimization (7 papers). Arvind Dhaka collaborates with scholars based in India, China and United States. Arvind Dhaka's co-authors include Amita Nandal, Arpit Kumar Sharma, Kemal Polat, Adi Alhudhaif, Fayadh Alenezi, Hamurabi Gamboa-Rosales, Liang Zhou, Vidhyacharan Bhaskar, Jorge I. Galván-Tejada and Carlos E. Galván-Tejada and has published in prestigious journals such as Scientific Reports, IEEE Access and Applied Soft Computing.

In The Last Decade

Arvind Dhaka

40 papers receiving 352 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arvind Dhaka India 10 169 118 89 44 42 48 375
Amita Nandal India 10 189 1.1× 113 1.0× 82 0.9× 40 0.9× 36 0.9× 36 370
Debanjan Konar India 11 77 0.5× 32 0.3× 221 2.5× 51 1.2× 54 1.3× 31 433
Heewon Kim South Korea 7 197 1.2× 30 0.3× 250 2.8× 65 1.5× 35 0.8× 20 449
Zhengui Xue China 12 202 1.2× 19 0.2× 346 3.9× 27 0.6× 59 1.4× 32 615
Sandip Dey India 10 181 1.1× 18 0.2× 242 2.7× 42 1.0× 29 0.7× 31 436
Ashima Anand India 18 855 5.1× 85 0.7× 120 1.3× 33 0.8× 42 1.0× 45 1.0k
Virendra P. Vishwakarma India 17 601 3.6× 27 0.2× 232 2.6× 47 1.1× 12 0.3× 92 774
Feng Shao China 9 105 0.6× 22 0.2× 81 0.9× 18 0.4× 56 1.3× 29 315
Poonam Sharma India 12 161 1.0× 9 0.1× 105 1.2× 28 0.6× 35 0.8× 51 439

Countries citing papers authored by Arvind Dhaka

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Arvind Dhaka

This figure shows the co-authorship network connecting the top 25 collaborators of Arvind Dhaka. A scholar is included among the top collaborators of Arvind Dhaka 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 Arvind Dhaka. Arvind Dhaka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Sharma, Arpit Kumar, et al.. (2025). Diagnosis of cervical cancer using CNN deep learning model with transfer learning approaches. Biomedical Signal Processing and Control. 105. 107639–107639. 1 indexed citations
2.
Dhaka, Arvind, et al.. (2025). An Explainable Deep Learning Framework for Usable and Secure Image Steganography. 1–6. 1 indexed citations
3.
Anand, Vatsala, et al.. (2025). Deep learning model for early acute lymphoblastic leukemia detection using microscopic images. Scientific Reports. 15(1). 29147–29147. 1 indexed citations
4.
Rathore, Pramod Singh, Abhishek Kumar, Amita Nandal, Arvind Dhaka, & Arpit Kumar Sharma. (2025). A feature explainability-based deep learning technique for diabetic foot ulcer identification. Scientific Reports. 15(1). 6758–6758. 3 indexed citations
5.
Dhaka, Arvind, et al.. (2025). Secure data transmission through fractal-based cryptosystem: a Noor iteration approach. Scientific Reports. 15(1). 22206–22206.
6.
Dhaka, Arvind, et al.. (2024). Breast tumor detection using multi‐feature block based neural network by fusion of CT and MRI images. Computational Intelligence. 40(3).
7.
Sharma, Arpit Kumar, Amita Nandal, Arvind Dhaka, et al.. (2023). Brain tumor classification using the modified ResNet50 model based on transfer learning. Biomedical Signal Processing and Control. 86. 105299–105299. 67 indexed citations
8.
Polák, Ladislav, et al.. (2023). Single Frequency Networks for DVB-T2: Analysis of Real Case Scenarios in Czech Republic. 16. 1–6. 1 indexed citations
9.
Sharma, Arpit Kumar, Amita Nandal, Arvind Dhaka, et al.. (2023). HOG transformation based feature extraction framework in modified Resnet50 model for brain tumor detection. Biomedical Signal Processing and Control. 84. 104737–104737. 43 indexed citations
10.
Zhou, Liang, et al.. (2023). Artificial Neural Network Dual Hesitant Fermatean Fuzzy Implementation in Transportation of COVID-19 Vaccine. Journal of Organizational and End User Computing. 35(2). 1–23. 7 indexed citations
11.
12.
Zhou, Liang, Amita Nandal, Todor Ganchev, & Arvind Dhaka. (2022). Breast cancer detection by fusion of deep features with CNN extracted features. International Journal of Intelligent Systems Technologies and Applications. 20(6). 510–510. 2 indexed citations
13.
Sharma, M. K., et al.. (2022). Post-symptomatic detection of COVID-2019 grade based mediative fuzzy projection. Computers & Electrical Engineering. 101. 108028–108028. 11 indexed citations
14.
Sharma, Arpit Kumar, Amita Nandal, Arvind Dhaka, & Amit Sinhal. (2022). A Novel Brain Tumor Classification Algorithm using SVM Classifier. International Journal of Emerging Technology and Advanced Engineering. 12(11). 175–182. 1 indexed citations
15.
Nandal, Amita, Arvind Dhaka, Liang Zhou, & Todor Ganchev. (2022). Breast cancer detection by fusion of deep features with CNN extracted features. International Journal of Intelligent Systems Technologies and Applications. 20(6). 510–510. 1 indexed citations
16.
Nandal, Amita, et al.. (2022). Fractal Feature Based Image Resolution Enhancement Using Wavelet–Fractal Transformation in Gradient Domain. Journal of Circuits Systems and Computers. 32(2). 5 indexed citations
17.
Dhaka, Arvind, et al.. (2022). Energy Efficiency Optimization for D2D Underlay Communication in Distributed Antenna System over Composite Fading Channels. Radioengineering. 31(3). 440–448. 1 indexed citations
18.
Sharma, Arpit Kumar, et al.. (2021). Medical Image Classification Techniques and Analysis Using Deep Learning Networks: A Review. Studies in computational intelligence. 233–258. 21 indexed citations
19.
Dhaka, Arvind, et al.. (2020). A DCT Fractional Bit Replacement Based Dual Watermarking Algorithmfor Image Authentication. Recent Advances in Computer Science and Communications. 14(9). 2899–2919. 2 indexed citations
20.
Nandal, Amita, Vidhyacharan Bhaskar, & Arvind Dhaka. (2018). Contrast‐based image enhancement algorithm using grey‐scale and colour space. IET Signal Processing. 12(4). 514–521. 15 indexed citations

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.

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