Navaneeth Bodla
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 10%
- Artificial Intelligence
- Media Technology
- Information Systems
- Co-authors
- Rama ChellappaJun-Cheng ChenCarlos D. CastilloVishal M. PatelAnkan BansalSwami SankaranarayananRajeev RanjanBharat Singh
- Topics
- Face recognition and analysis (5 papers)Generative Adversarial Networks and Image Synthesis (3 papers)Biometric Identification and Security (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Signal Processing MagazinearXiv (Cornell University)
- Partner nations
- United StatesGermany
In The Last Decade
Navaneeth Bodla
9 papers receiving 268 citations
Peers
Comparison fields: 5 of 80
- Computer Vision and Pattern Recognition 209
- Signal Processing 56
- Artificial Intelligence 50
- Media Technology 17
- Information Systems 15
Countries citing papers authored by Navaneeth Bodla
This map shows the geographic impact of Navaneeth Bodla'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 Navaneeth Bodla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Navaneeth Bodla more than expected).
Fields of papers citing papers by Navaneeth Bodla
This network shows the impact of papers produced by Navaneeth Bodla. 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 Navaneeth Bodla. The network helps show where Navaneeth Bodla may publish in the future.
Co-authorship network of co-authors of Navaneeth Bodla
This figure shows the co-authorship network connecting the top 25 collaborators of Navaneeth Bodla. A scholar is included among the top collaborators of Navaneeth Bodla 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 Navaneeth Bodla. Navaneeth Bodla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 21 | |
| 3 | 5 | |
| 4 | 21 | |
| 5 | 128 | |
| 6 | Soft Sampling for Robust Object Detection. | 1 |
| 7 | Improving Object Detection With One Line of Code. | 60 |
| 8 | 32 | |
| 9 | 5 |
About Navaneeth Bodla
Navaneeth Bodla is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 9 papers that have together received 283 indexed citations. Recurring topics across this work include Face recognition and analysis (5 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Biometric Identification and Security (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (209 citations), Signal Processing (56 citations) and Media Technology (17 citations). Navaneeth Bodla has collaborated with scholars based in United States and Germany. Frequent co-authors include Rama Chellappa, Jun-Cheng Chen, Carlos D. Castillo, Vishal M. Patel, Ankan Bansal, Swami Sankaranarayanan, Rajeev Ranjan, Bharat Singh, Larry S. Davis and Hongyu Xu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Signal Processing Magazine and arXiv (Cornell University).
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.