Ayush Dogra

2.4k total citations · 1 hit paper
130 papers, 1.4k citations indexed

About

Ayush Dogra is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Biomedical Engineering. According to data from OpenAlex, Ayush Dogra has authored 130 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Computer Vision and Pattern Recognition, 55 papers in Media Technology and 19 papers in Biomedical Engineering. Recurrent topics in Ayush Dogra's work include Advanced Image Fusion Techniques (52 papers), Image and Signal Denoising Methods (36 papers) and Image Enhancement Techniques (16 papers). Ayush Dogra is often cited by papers focused on Advanced Image Fusion Techniques (52 papers), Image and Signal Denoising Methods (36 papers) and Image Enhancement Techniques (16 papers). Ayush Dogra collaborates with scholars based in India, United States and Iraq. Ayush Dogra's co-authors include Bhawna Goyal, Sunil Agrawal, B.S. Sohi, Dawa Chyophel Lepcha, Apoorav Maulik Sharma, Vishal Goyal, Chirag Ahuja, Sanjeev Kumar, Vinay Kukreja and S. Prasad and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ayush Dogra

103 papers receiving 1.3k citations

Hit Papers

Image denoising review: From classical to state-of-the-ar... 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Image denoising review: From classical to state-of-the-art approaches
    2019 289 citations Bhawna Goyal, Ayush Dogra et al. Information Fusion profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ayush Dogra India 18 847 685 168 124 121 130 1.4k
Bhawna Goyal India 17 782 0.9× 634 0.9× 151 0.9× 101 0.8× 112 0.9× 111 1.4k
Cheolkon Jung China 24 1.8k 2.1× 700 1.0× 146 0.9× 180 1.5× 96 0.8× 203 2.4k
Sunil Agrawal India 18 593 0.7× 508 0.7× 126 0.8× 169 1.4× 81 0.7× 96 1.4k
Xuming Zhang China 20 661 0.8× 487 0.7× 168 1.0× 185 1.5× 196 1.6× 93 1.2k
Umme Sara Bangladesh 5 544 0.6× 211 0.3× 141 0.8× 144 1.2× 135 1.1× 8 1.0k
Mehran Yazdi Iran 20 877 1.0× 379 0.6× 283 1.7× 240 1.9× 233 1.9× 113 1.6k
Jianqing Zhu China 25 1.4k 1.7× 423 0.6× 152 0.9× 321 2.6× 110 0.9× 97 1.9k
Azeddine Beghdadi France 25 1.9k 2.2× 751 1.1× 151 0.9× 202 1.6× 88 0.7× 194 2.5k
Guang Deng Australia 18 1.1k 1.3× 368 0.5× 69 0.4× 137 1.1× 63 0.5× 123 1.6k

Countries citing papers authored by Ayush Dogra

Since Specialization
Citations

This map shows the geographic impact of Ayush Dogra'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 Ayush Dogra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ayush Dogra more than expected).

Fields of papers citing papers by Ayush Dogra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ayush Dogra. 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 Ayush Dogra. The network helps show where Ayush Dogra may publish in the future.

Co-authorship network of co-authors of Ayush Dogra

This figure shows the co-authorship network connecting the top 25 collaborators of Ayush Dogra. A scholar is included among the top collaborators of Ayush Dogra 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 Ayush Dogra. Ayush Dogra 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.
Goyal, Bhawna, et al.. (2025). Artificial intelligence in dermatology: a systematic review of skin cancer detection and classification. Engineering Research Express. 7(4). 42202–42202.
2.
3.
Sharma, Shagun, Kalpna Guleria, & Ayush Dogra. (2025). FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets. Current Medical Imaging Formerly Current Medical Imaging Reviews. 21. e15734056333970–e15734056333970.
4.
Lepcha, Dawa Chyophel, et al.. (2025). Deep Learning in Medical Image Analysis: A Comprehensive Review of Algorithms, Trends, Applications, and Challenges. Computer Modeling in Engineering & Sciences. 145(2). 1487–1573.
5.
Goyal, Bhawna, Ayush Dogra, Mohammed Ahmed Mustafa, et al.. (2024). Image segmentation review: Theoretical background and recent advances. Information Fusion. 114. 102608–102608. 18 indexed citations
6.
Mehta, Shiva, et al.. (2024). Advancing IoT Security through Federated Learning: A Comprehensive Approach. 561–566. 4 indexed citations
7.
Lepcha, Dawa Chyophel, et al.. (2024). A Robust Medical Image Fusion Based on Synthetic Focusing Degree Criterion and Special Kernel Set for Clinical Diagnosis. Journal of Computer Science. 20(4). 389–399. 2 indexed citations
8.
Dogra, Ayush, Bhawna Goyal, Dawa Chyophel Lepcha, et al.. (2024). Effective image fusion strategies in scientific signal processing disciplines: Application to cancer and carcinoma treatment planning. PLoS ONE. 19(7). e0301441–e0301441. 1 indexed citations
9.
Goyal, Bhawna, et al.. (2024). Detailed-based dictionary learning for low-light image enhancement using camera response model for industrial applications. Scientific Reports. 14(1). 17122–17122. 3 indexed citations
10.
Mehta, Shiva, Ajay P. Sharma, Ayush Dogra, & Shanmugasundaram Hariharan. (2024). The Impact of Federated Learning on IoT Security: An Empirical Analysis. 462–466. 6 indexed citations
11.
Goyal, Bhawna, Ayush Dogra, Dawa Chyophel Lepcha, et al.. (2023). Recent advances in image dehazing: Formal analysis to automated approaches. Information Fusion. 104. 102151–102151. 10 indexed citations
12.
Lepcha, Dawa Chyophel, et al.. (2023). A constructive non-local means algorithm for low-dose computed tomography denoising with morphological residual processing. PLoS ONE. 18(9). e0291911–e0291911. 8 indexed citations
13.
Goyal, Bhawna, et al.. (2023). Cloud Computing Improved Clustering using Intrusion Detection. 15. 1–5. 3 indexed citations
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Goyal, Bhawna, et al.. (2023). Citrus fruit content and disease detection using adaptive contrast enhancement. Materials Today Proceedings. 1 indexed citations
17.
Dogra, Ayush, et al.. (2021). NIR-based Sensing System for Non-invasive Detection of Hemoglobin forPoint-of-care Applications. Current Medical Imaging Formerly Current Medical Imaging Reviews. 18(5). 532–545. 4 indexed citations
18.
Goyal, Bhawna, Ayush Dogra, Jasgurpreet Singh Chohan, & Anupma Gupta. (2021). Concurrent clinical optoacoustic and ultrasound imaging for mapping of breast tumor. Materials Today Proceedings. 48. 1451–1454. 2 indexed citations
19.
Dogra, Ayush, et al.. (2015). Medical Image Denoising by Bilateral Filtering & Pure-Let for Corrupted Poisson Images. 4(1). 100–103. 1 indexed citations
20.
Dogra, Ayush. (2014). Feature Based Matching of CT & MRI Brain Images. Journal of medical research/˜The œjournal of medical research. 13(2). 1 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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