Uddagiri Sirisha
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Plant Science
- Health Information Management top 10%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- S. Phani PraveenB. Sai ChandanaParvathaneni Naga SrinivasuAkash Kumar BhoiPaolo BarsocchiSai Srinivas VellelaThulasi BikkuChan Yeob Yeun
- Topics
- Sentiment Analysis and Opinion Mining (3 papers)Topic Modeling (3 papers)Advanced Neural Network Applications (3 papers)
In The Last Decade
Uddagiri Sirisha
15 papers receiving 257 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 79
- Computer Vision and Pattern Recognition 78
- Plant Science 34
- Health Information Management 22
- Radiology, Nuclear Medicine and Imaging 20
Countries citing papers authored by Uddagiri Sirisha
This map shows the geographic impact of Uddagiri Sirisha'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 Uddagiri Sirisha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uddagiri Sirisha more than expected).
Fields of papers citing papers by Uddagiri Sirisha
This network shows the impact of papers produced by Uddagiri Sirisha. 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 Uddagiri Sirisha. The network helps show where Uddagiri Sirisha may publish in the future.
Co-authorship network of co-authors of Uddagiri Sirisha
This figure shows the co-authorship network connecting the top 25 collaborators of Uddagiri Sirisha. A scholar is included among the top collaborators of Uddagiri Sirisha 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 Uddagiri Sirisha. Uddagiri Sirisha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 12 | |
| 9 | 31 | |
| 10 | 1 | |
| 11 | 6 | |
| 12 | Statistical Analysis of Design Aspects of Various YOLO-Based Deep Learning Models for Object Detectionbreakdown → | 108 |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 21 | |
| 16 | 0 | |
| 17 | 47 | |
| 18 | 6 | |
| 19 | 20 | |
| 20 | 13 |
About Uddagiri Sirisha
Uddagiri Sirisha is a scholar working on Health Information Management, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 280 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (3 papers), Topic Modeling (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Health Information Management (22 citations), Computer Vision and Pattern Recognition (78 citations) and Health Informatics (4 citations). Uddagiri Sirisha has collaborated with scholars based in India, Malaysia and Brazil. Frequent co-authors include S. Phani Praveen, B. Sai Chandana, Parvathaneni Naga Srinivasu, Akash Kumar Bhoi, Paolo Barsocchi, Sai Srinivas Vellela, Thulasi Bikku, Chan Yeob Yeun, Mohammad Kamrul Hasan and Gabriel Avelino Sampedro. Their work appears in journals such as Scientific Reports, Sensors and Frontiers in Medicine.
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.