Sandeep Kanumuri
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Computer Networks and Communications
- Sociology and Political Science
- Electrical and Electronic Engineering
- Co-authors
- Pamela C. CosmanAmy R. ReibmanVinay A. VaishampayanTing‐Lan LinSwaminathan SubramanianYuan ZhiM. Reha CivanlarUlaş C. Kozat
- Topics
- Video Coding and Compression Technologies (8 papers)Image and Video Quality Assessment (7 papers)Advanced Image Processing Techniques (4 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Networks and Communications
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Circuits and Systems for Video TechnologyIEEE Transactions on Multimedia
- Partner nations
- United StatesFranceIndia
In The Last Decade
Sandeep Kanumuri
11 papers receiving 304 citations
Peers
Comparison fields: 5 of 24
- Computer Vision and Pattern Recognition 286
- Signal Processing 211
- Computer Networks and Communications 53
- Sociology and Political Science 32
- Electrical and Electronic Engineering 32
Countries citing papers authored by Sandeep Kanumuri
This map shows the geographic impact of Sandeep Kanumuri'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 Sandeep Kanumuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandeep Kanumuri more than expected).
Fields of papers citing papers by Sandeep Kanumuri
This network shows the impact of papers produced by Sandeep Kanumuri. 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 Sandeep Kanumuri. The network helps show where Sandeep Kanumuri may publish in the future.
Co-authorship network of co-authors of Sandeep Kanumuri
This figure shows the co-authorship network connecting the top 25 collaborators of Sandeep Kanumuri. A scholar is included among the top collaborators of Sandeep Kanumuri 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 Sandeep Kanumuri. Sandeep Kanumuri 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 | 3 | |
| 3 | 22 | |
| 4 | 67 | |
| 5 | 22 | |
| 6 | 9 | |
| 7 | 7 | |
| 8 | 6 | |
| 9 | 110 | |
| 10 | 51 | |
| 11 | Packet loss visibility and packet prioritization in digital videos | 1 |
| 12 | 26 |
About Sandeep Kanumuri
Sandeep Kanumuri is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 12 papers that have together received 324 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (8 papers), Image and Video Quality Assessment (7 papers) and Advanced Image Processing Techniques (4 papers). The work is most often cited by research in Signal Processing (211 citations), Computer Vision and Pattern Recognition (286 citations) and Computer Networks and Communications (53 citations). Sandeep Kanumuri has collaborated with scholars based in United States, France and India. Frequent co-authors include Pamela C. Cosman, Amy R. Reibman, Vinay A. Vaishampayan, Ting‐Lan Lin, Swaminathan Subramanian, Yuan Zhi, M. Reha Civanlar, Ulaş C. Kozat, Özgür Harmancı and Onur G. Guleryuz. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Multimedia.
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.