Mandar Dixit
Impact in
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- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Media Technology top 10%
- Remote-Sensing Image Classification
Papers in
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- Advanced Image and Video Retrieval Techniques 5
- Advanced Neural Network Applications 2
- Image Retrieval and Classification Techniques 2
- Video Surveillance and Tracking Methods 1
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- Domain Adaptation and Few-Shot Learning 3
- Advanced Graph Neural Networks 1
- Co-authors
- Nuno Vasconcelos (6 shared papers)Nikhil Rasiwasia (3 shared papers)Dashan Gao (1 shared paper)Si Chen (1 shared paper)Roland Kwitt (2 shared papers)Xudong Wang (1 shared paper)Bo Liu (1 shared paper)Yunsheng Li (1 shared paper)
- Journals
- Neural Information Processing Systems (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Mandar Dixit
8 papers receiving 268 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 207
- Media Technology 48
- Artificial Intelligence 82
- Computational Mathematics 1
- Geology 8
Countries citing papers authored by Mandar Dixit
This map shows the geographic impact of Mandar Dixit'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 Mandar Dixit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mandar Dixit more than expected).
Fields of papers citing papers by Mandar Dixit
This network shows the impact of papers produced by Mandar Dixit. 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 Mandar Dixit. The network helps show where Mandar Dixit may publish in the future.
Co-authors
The 9 scholars most cited alongside Mandar Dixit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 99 | |
| 2 | 2018 | 71 | |
| 3 | 2017 | 38 | |
| 4 | 2011 | 32 | |
| 5 | Object based scene representations using fisher scores of local subspace projections | 2016 | 15 |
| 6 | 2019 | 13 | |
| 7 | 2013 | 2 | |
| 8 | 2014 | 1 |
About Mandar Dixit
Mandar Dixit is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, General Health Professions and Computational Theory and Mathematics, having authored 8 papers that have together received 271 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (5 papers), Remote-Sensing Image Classification (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Advanced Neural Network Applications (2 papers), Image Retrieval and Classification Techniques (2 papers), Topological and Geometric Data Analysis (1 paper), Advanced Graph Neural Networks (1 paper) and Video Surveillance and Tracking Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (207 citations), Media Technology (48 citations), Artificial Intelligence (82 citations), Computational Mathematics (1 citation) and Geology (8 citations). Mandar Dixit has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Nuno Vasconcelos, Nikhil Rasiwasia, Dashan Gao, Si Chen, Roland Kwitt, Xudong Wang, Bo Liu, Yunsheng Li and Marc Niethammer. Their work appears in journals such as Neural Information Processing Systems and arXiv (Cornell University).
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.