Kamred Udham Singh
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Networks and Communications top 10%
- Neurology top 10%
- Co-authors
- Ankit KumarIndrajeet KumarAbhishek KumarChandradeep BhattTeekam SinghV. VijayakumarSaroj Kumar PandeyAchintya Singhal
- Topics
- Digital Media Forensic Detection (19 papers)Advanced Steganography and Watermarking Techniques (19 papers)COVID-19 diagnosis using AI (14 papers)
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- IndiaSaudi ArabiaTaiwan
In The Last Decade
Kamred Udham Singh
92 papers receiving 668 citations
Peers
Comparison fields: 5 of 119
- Computer Vision and Pattern Recognition 245
- Artificial Intelligence 165
- Radiology, Nuclear Medicine and Imaging 111
- Computer Networks and Communications 75
- Neurology 69
Countries citing papers authored by Kamred Udham Singh
This map shows the geographic impact of Kamred Udham Singh'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 Kamred Udham Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kamred Udham Singh more than expected).
Fields of papers citing papers by Kamred Udham Singh
This network shows the impact of papers produced by Kamred Udham Singh. 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 Kamred Udham Singh. The network helps show where Kamred Udham Singh may publish in the future.
Co-authorship network of co-authors of Kamred Udham Singh
This figure shows the co-authorship network connecting the top 25 collaborators of Kamred Udham Singh. A scholar is included among the top collaborators of Kamred Udham Singh 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 Kamred Udham Singh. Kamred Udham Singh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 14 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 10 | |
| 13 | 3 | |
| 14 | 20 | |
| 15 | 1 | |
| 16 | 15 | |
| 17 | 7 | |
| 18 | 4 | |
| 19 | Channelized Noise Augmentation to Endorse DICOM Medical Image for Diagnosing | 7 |
| 20 | Color Image Watermarking Scheme Based on QR Factorization and DWT with Compatibility Analysis on Different Wavelet Filters | 8 |
About Kamred Udham Singh
Kamred Udham Singh is a scholar working on Computer Vision and Pattern Recognition, Neurology and Health Information Management, having authored 114 papers that have together received 720 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (19 papers), Advanced Steganography and Watermarking Techniques (19 papers) and COVID-19 diagnosis using AI (14 papers). The work is most often cited by research in Health Informatics (23 citations), Computer Vision and Pattern Recognition (245 citations) and Health Information Management (40 citations). Kamred Udham Singh has collaborated with scholars based in India, Saudi Arabia and Taiwan. Frequent co-authors include Ankit Kumar, Indrajeet Kumar, Abhishek Kumar, Chandradeep Bhatt, Teekam Singh, V. Vijayakumar, Saroj Kumar Pandey, Achintya Singhal, Mamoon Rashid and Turki Aljrees. Their work appears in journals such as Scientific Reports, IEEE Access and Sensors.
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.