Vinay Kumar Verma
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- Digital Media Forensic Detection 6
- Multimodal Machine Learning Applications 5
- Advanced Neural Network Applications 5
- Advanced Steganography and Watermarking Techniques 3
- Advanced Image Processing Techniques 3
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning 13
- Media Technology top 10%
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- Tribology and Wear Analysis 3
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- Lubricants and Their Additives 3
- Co-authors
- Piyush RaiNitin KhannaLawrence CarinPravendra SinghNikita AgarwalN.B. SinghT. Sonamani SinghYunchen Pu
- Journals
- Construction and Building Materials (1 paper)International Journal of Computer Vision (1 paper)Journal of Alloys and Compounds (1 paper)
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Vinay Kumar Verma
41 papers receiving 459 citations
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 215
- Artificial Intelligence 186
- Media Technology 32
- Signal Processing 28
- Metals and Alloys 6
Countries citing papers authored by Vinay Kumar Verma
This map shows the geographic impact of Vinay Kumar Verma'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 Vinay Kumar Verma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vinay Kumar Verma more than expected).
Fields of papers citing papers by Vinay Kumar Verma
This network shows the impact of papers produced by Vinay Kumar Verma. 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 Vinay Kumar Verma. The network helps show where Vinay Kumar Verma may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vinay Kumar Verma, 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 | 2025 | 5 | |
| 2 | 2025 | 3 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 3 | |
| 7 | 2023 | 31 | |
| 8 | 2023 | 13 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 4 | |
| 11 | Comparative Study of Cloud Computing and Edge Computing: Three Level Architecture Models and Security Challenges | 2021 | 5 |
| 12 | Calibrating CNNs for Lifelong Learning | 2020 | 27 |
| 13 | 2020 | 10 | |
| 14 | CNN-based System for Speaker Independent Cell-Phone Identification from Recorded Audio | 2019 | 7 |
| 15 | 2019 | 14 | |
| 16 | 2018 | 37 | |
| 17 | A Probabilistic Framework for Multi-Label Learning with Unseen Labels. | 2017 | 2 |
| 18 | 2013 | 2 | |
| 19 | 2011 | 6 | |
| 20 | 1988 | 24 |
About Vinay Kumar Verma
Vinay Kumar Verma is a scholar working on Complementary and Manual Therapy, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 42 papers that have together received 478 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (13 papers), Digital Media Forensic Detection (6 papers), Multimodal Machine Learning Applications (5 papers), Advanced Neural Network Applications (5 papers), Tribology and Wear Analysis (3 papers), Lubricants and Their Additives (3 papers), Advanced Steganography and Watermarking Techniques (3 papers) and Advanced Image Processing Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (215 citations), Artificial Intelligence (186 citations) and Media Technology (32 citations). Vinay Kumar Verma has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Piyush Rai, Nitin Khanna, Lawrence Carin, Pravendra Singh, Nikita Agarwal, N.B. Singh, T. Sonamani Singh, Yunchen Pu, Changyou Chen and Wenlin Wang. Their work appears in journals such as Construction and Building Materials, International Journal of Computer Vision and Journal of Alloys and Compounds.
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.