Vasundhara Acharya
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Plant Science
- Media Technology top 10%
- Co-authors
- Preetham KumarVinayakumar RaviTuan D. PhamMamoun AlazabKrishna PrakashChinmay ChakrabortyWattana ViriyasitavatKrishnaraj Chadaga
- Topics
- Digital Imaging for Blood Diseases (8 papers)AI in cancer detection (6 papers)Smart Agriculture and AI (4 papers)
- Partner nations
- IndiaSaudi ArabiaUnited States
In The Last Decade
Vasundhara Acharya
24 papers receiving 399 citations
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 158
- Radiology, Nuclear Medicine and Imaging 148
- Artificial Intelligence 131
- Plant Science 81
- Media Technology 44
Countries citing papers authored by Vasundhara Acharya
This map shows the geographic impact of Vasundhara Acharya'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 Vasundhara Acharya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vasundhara Acharya more than expected).
Fields of papers citing papers by Vasundhara Acharya
This network shows the impact of papers produced by Vasundhara Acharya. 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 Vasundhara Acharya. The network helps show where Vasundhara Acharya may publish in the future.
Co-authorship network of co-authors of Vasundhara Acharya
This figure shows the co-authorship network connecting the top 25 collaborators of Vasundhara Acharya. A scholar is included among the top collaborators of Vasundhara Acharya 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 Vasundhara Acharya. Vasundhara Acharya 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 | 11 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 65 | |
| 6 | 2 | |
| 7 | 34 | |
| 8 | 15 | |
| 9 | 20 | |
| 10 | 8 | |
| 11 | 6 | |
| 12 | Text based machine learning using discriminative classifiers | 0 |
| 13 | An Innovative Lossless Image and Video Compression Using Revised S Transformation | 2 |
| 14 | 52 | |
| 15 | 8 | |
| 16 | 5 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | 4 | |
| 20 | 49 |
About Vasundhara Acharya
Vasundhara Acharya is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 25 papers that have together received 417 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (8 papers), AI in cancer detection (6 papers) and Smart Agriculture and AI (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (158 citations), Health Informatics (10 citations) and Biophysics (39 citations). Vasundhara Acharya has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include Preetham Kumar, Vinayakumar Ravi, Tuan D. Pham, Mamoun Alazab, Krishna Prakash, Chinmay Chakraborty, Wattana Viriyasitavat, Krishnaraj Chadaga, Sandeep Kautish and Gaurav Dhiman. Their work appears in journals such as Scientific Reports, IEEE Access and IEEE Transactions on Engineering Management.
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.