Kartik Thakral
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Pulmonary and Respiratory Medicine
- Health Information Management top 5%
- Co-authors
- Ankush MittalRahul NijhawanMayank VatsaRicha SinghHarsh AgarwalCristian Canton FerrerTal HassnerAnkur Gupta
- Topics
- Generative Adversarial Networks and Image Synthesis (4 papers)Face recognition and analysis (3 papers)Digital Media Forensic Detection (3 papers)
- Partner nations
- IndiaTaiwanUnited States
In The Last Decade
Kartik Thakral
11 papers receiving 350 citations
Hit Papers
Peers
Comparison fields: 5 of 58
- Radiology, Nuclear Medicine and Imaging 227
- Artificial Intelligence 164
- Computer Vision and Pattern Recognition 125
- Pulmonary and Respiratory Medicine 53
- Health Information Management 29
Countries citing papers authored by Kartik Thakral
This map shows the geographic impact of Kartik Thakral'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 Kartik Thakral with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kartik Thakral more than expected).
Fields of papers citing papers by Kartik Thakral
This network shows the impact of papers produced by Kartik Thakral. 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 Kartik Thakral. The network helps show where Kartik Thakral may publish in the future.
Co-authorship network of co-authors of Kartik Thakral
This figure shows the co-authorship network connecting the top 25 collaborators of Kartik Thakral. A scholar is included among the top collaborators of Kartik Thakral 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 Kartik Thakral. Kartik Thakral is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 13 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 37 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 14 | |
| 11 | 14 | |
| 12 | 3 | |
| 13 | 7 | |
| 14 | Pneumonia Detection Using CNN based Feature Extractionbreakdown → | 266 |
About Kartik Thakral
Kartik Thakral is a scholar working on Health Informatics, General Social Sciences and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 370 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (4 papers), Face recognition and analysis (3 papers) and Digital Media Forensic Detection (3 papers). The work is most often cited by research in Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (227 citations) and Health Information Management (29 citations). Kartik Thakral has collaborated with scholars based in India, Taiwan and United States. Frequent co-authors include Ankush Mittal, Rahul Nijhawan, Mayank Vatsa, Richa Singh, Harsh Agarwal, Cristian Canton Ferrer, Tal Hassner, Harsh Agarwal, Ankur Gupta and Aakarsh Malhotra. Their work appears in journals such as PLoS ONE, Nature Machine Intelligence and IEEE Transactions on Artificial Intelligence.
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.