Richa Gupta
- Dermatology top 5%
- Skin Protection and Aging 3
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- Chaos-based Image/Signal Encryption 15
- Advanced Steganography and Watermarking Techniques 11
- Advanced Data Compression Techniques 5
- Digital Imaging for Blood Diseases 3
- Digital Media Forensic Detection 3
- Pathology and Forensic Medicine top 10%
- Human-Computer Interaction top 10%
- Media Technology top 10%
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- Mathematical Dynamics and Fractals 6
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- AI in cancer detection 3
- Co-authors
- Rebecca S. MasonGary M. HallidayShivashni DeoKatie M. DixonAbhilasha SinghMichael D. SlaterVivienne E. ReeveSarika Jain
- Journals
- Journal of Investigative Dermatology (1 paper)The Journal of Steroid Biochemistry and Molecular Biology (1 paper)Alexandria Engineering Journal (1 paper)
- Partner nations
- IndiaUnited Arab EmiratesAustralia
In The Last Decade
Richa Gupta
44 papers receiving 599 citations
Peers
Comparison fields: 5 of 121
- Dermatology 166
- Computer Vision and Pattern Recognition 218
- Pathology and Forensic Medicine 127
- Human-Computer Interaction 30
- Media Technology 30
Countries citing papers authored by Richa Gupta
This map shows the geographic impact of Richa Gupta'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 Richa Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richa Gupta more than expected).
Fields of papers citing papers by Richa Gupta
This network shows the impact of papers produced by Richa Gupta. 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 Richa Gupta. The network helps show where Richa Gupta may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Richa Gupta, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2023 | 0 | |
| 3 | 2023 | 0 | |
| 4 | 2022 | 61 | |
| 5 | 2022 | 2 | |
| 6 | 2021 | 1 | |
| 7 | 2020 | 1 | |
| 8 | 2019 | 3 | |
| 9 | Analysis and Comparison of Various Fully Homomorphic Encryption Techniques | 2019 | 12 |
| 10 | 2019 | 8 | |
| 11 | 2019 | 0 | |
| 12 | 2019 | 2 | |
| 13 | 2018 | 1 | |
| 14 | 2018 | 2 | |
| 15 | 2017 | 13 | |
| 16 | 2017 | 17 | |
| 17 | 2016 | 5 | |
| 18 | 2012 | 57 | |
| 19 | 2006 | 120 | |
| 20 | 2004 | 80 |
About Richa Gupta
Richa Gupta is a scholar working on Computer Vision and Pattern Recognition, Mathematical Physics and Human-Computer Interaction, having authored 49 papers that have together received 634 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (15 papers), Advanced Steganography and Watermarking Techniques (11 papers), Mathematical Dynamics and Fractals (6 papers), Advanced Data Compression Techniques (5 papers), Digital Imaging for Blood Diseases (3 papers), Skin Protection and Aging (3 papers), AI in cancer detection (3 papers) and Digital Media Forensic Detection (3 papers). The work is most often cited by research in Dermatology (166 citations), Computer Vision and Pattern Recognition (218 citations) and Pathology and Forensic Medicine (127 citations). Richa Gupta has collaborated with scholars based in India, United Arab Emirates and Australia. Frequent co-authors include Rebecca S. Mason, Gary M. Halliday, Shivashni Deo, Katie M. Dixon, Abhilasha Singh, Michael D. Slater, Vivienne E. Reeve, Sarika Jain, Anurag Mishra and Rajesh Kumar Tyagi. Their work appears in journals such as Journal of Investigative Dermatology, The Journal of Steroid Biochemistry and Molecular Biology and Alexandria Engineering Journal.
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.