Ramakrishna Kakarala
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Signal Processing top 10%
- Computational Mechanics
- Biomedical Engineering
- Co-authors
- Philip OgunbonaZ. BaharavAlfred O. HeroRamya HebbalaguppeGeoffrey IversonMark AndrewsWilliam R. UttalQian Kemao
- Topics
- Image Retrieval and Classification Techniques (11 papers)Image and Signal Denoising Methods (10 papers)Blind Source Separation Techniques (8 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Information TheoryIEEE Transactions on Image Processing
- Partner nations
- SingaporeUnited StatesNew Zealand
In The Last Decade
Ramakrishna Kakarala
51 papers receiving 520 citations
Peers
Comparison fields: 5 of 82
- Computer Vision and Pattern Recognition 359
- Media Technology 97
- Signal Processing 62
- Computational Mechanics 60
- Biomedical Engineering 58
Countries citing papers authored by Ramakrishna Kakarala
This map shows the geographic impact of Ramakrishna Kakarala'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 Ramakrishna Kakarala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramakrishna Kakarala more than expected).
Fields of papers citing papers by Ramakrishna Kakarala
This network shows the impact of papers produced by Ramakrishna Kakarala. 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 Ramakrishna Kakarala. The network helps show where Ramakrishna Kakarala may publish in the future.
Co-authorship network of co-authors of Ramakrishna Kakarala
This figure shows the co-authorship network connecting the top 25 collaborators of Ramakrishna Kakarala. A scholar is included among the top collaborators of Ramakrishna Kakarala 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 Ramakrishna Kakarala. Ramakrishna Kakarala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 21 | |
| 4 | 11 | |
| 5 | 23 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | Completeness of bispectrum on compact groups | 2 |
| 11 | 3 | |
| 12 | 42 | |
| 13 | 93 | |
| 14 | 1 | |
| 15 | 20 | |
| 16 | 8 | |
| 17 | 40 | |
| 18 | Triple correlation on groups | 14 |
| 19 | 6 | |
| 20 | 15 |
About Ramakrishna Kakarala
Ramakrishna Kakarala is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 56 papers that have together received 549 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (11 papers), Image and Signal Denoising Methods (10 papers) and Blind Source Separation Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (359 citations), Media Technology (97 citations) and Human-Computer Interaction (38 citations). Ramakrishna Kakarala has collaborated with scholars based in Singapore, United States and New Zealand. Frequent co-authors include Philip Ogunbona, Z. Baharav, Alfred O. Hero, Ramya Hebbalaguppe, Geoffrey Iverson, Mark Andrews, William R. Uttal, Qian Kemao, Bruce M. Bennett and J.A. Cadzow. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Information Theory and IEEE Transactions on Image Processing.
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.