Vaibhav Arora
About
In The Last Decade
Vaibhav Arora
10 papers receiving 387 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Radiology, Nuclear Medicine and Imaging 295
- Artificial Intelligence 201
- Computer Vision and Pattern Recognition 101
- Health Informatics 44
- Pulmonary and Respiratory Medicine 41
Countries citing papers authored by Vaibhav Arora
This map shows the geographic impact of Vaibhav Arora'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 Vaibhav Arora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vaibhav Arora more than expected).
Fields of papers citing papers by Vaibhav Arora
This network shows the impact of papers produced by Vaibhav Arora. 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 Vaibhav Arora. The network helps show where Vaibhav Arora may publish in the future.
Co-authorship network of co-authors of Vaibhav Arora
This figure shows the co-authorship network connecting the top 25 collaborators of Vaibhav Arora. A scholar is included among the top collaborators of Vaibhav Arora 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 Vaibhav Arora. Vaibhav Arora is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 39 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 28 | |
| 5 | 8 | |
| 6 | 23 | |
| 7 | Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study breakdown → | 277 |
| 8 | 16 | |
| 9 | A stacked sparse autoencoder based architecture for Punjabi and English spoken language classification using MFCC features | 2 |
| 10 | 7 |
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.