Aparna Taneja
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Media Technology top 5%
- Environmental Engineering
- Geology top 10%
- Co-authors
- Luca BallanMarc PollefeysPaul BeardsleyAmber ThomasGaurav ChaurasiaRoland SiegwartSundara Tejaswi DigumartiMilind Tambe
- Topics
- Advanced Bandit Algorithms Research (7 papers)Smart Grid Energy Management (4 papers)Advanced Vision and Imaging (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceLecture notes in computer scienceAI Magazine
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Aparna Taneja
12 papers receiving 224 citations
Peers
Comparison fields: 5 of 46
- Computer Vision and Pattern Recognition 149
- Aerospace Engineering 89
- Media Technology 58
- Environmental Engineering 54
- Geology 47
Countries citing papers authored by Aparna Taneja
This map shows the geographic impact of Aparna Taneja'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 Aparna Taneja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aparna Taneja more than expected).
Fields of papers citing papers by Aparna Taneja
This network shows the impact of papers produced by Aparna Taneja. 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 Aparna Taneja. The network helps show where Aparna Taneja may publish in the future.
Co-authorship network of co-authors of Aparna Taneja
This figure shows the co-authorship network connecting the top 25 collaborators of Aparna Taneja. A scholar is included among the top collaborators of Aparna Taneja 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 Aparna Taneja. Aparna Taneja 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 | 3 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 45 | |
| 11 | 32 | |
| 12 | 48 | |
| 13 | Motion capture of hands in action using discriminative salient points | 0 |
| 14 | 30 | |
| 15 | 65 |
About Aparna Taneja
Aparna Taneja is a scholar working on Management Science and Operations Research, Modeling and Simulation and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 237 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (7 papers), Smart Grid Energy Management (4 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Geology (47 citations), Computer Vision and Pattern Recognition (149 citations) and Media Technology (58 citations). Aparna Taneja has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Luca Ballan, Marc Pollefeys, Paul Beardsley, Amber Thomas, Gaurav Chaurasia, Roland Siegwart, Sundara Tejaswi Digumarti, Milind Tambe, Aparna Hegde and Shresth Verma. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Lecture notes in computer science and AI Magazine.
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.