Arvind Ganesh
- Computer Vision and Pattern Recognition top 0.05%
- Medical Image Segmentation Techniques 8
- Face and Expression Recognition 7
- Face recognition and analysis 5
- Image and Signal Denoising Methods 3
- Computational Mathematics top 0.5%
- Computational Mechanics top 0.05%
- Sparse and Compressive Sensing Techniques 13
- Media Technology top 0.1%
- Signal Processing top 0.1%
- Blind Source Separation Techniques 7
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- ZnO doping and properties 5
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- Groundwater and Watershed Analysis 3
Arvind Ganesh
39 papers receiving 11.6k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Computer Vision and Pattern Recognition 7.7k
- Computational Mathematics 158
- Computational Mechanics 4.8k
- Media Technology 2.0k
- Signal Processing 2.4k
Countries citing papers authored by Arvind Ganesh
This map shows the geographic impact of Arvind Ganesh'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 Arvind Ganesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arvind Ganesh more than expected).
Fields of papers citing papers by Arvind Ganesh
This network shows the impact of papers produced by Arvind Ganesh. 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 Arvind Ganesh. The network helps show where Arvind Ganesh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arvind Ganesh, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 7 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 0 | |
| 7 | 2022 | 1 | |
| 8 | 2019 | 1 | |
| 9 | 2019 | 23 | |
| 10 | 2018 | 1 | |
| 11 | Compressed Sensingbreakdown → | 2012 | 1142 |
| 12 | RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Imagesbreakdown → | 2012 | 580 |
| 13 | 2012 | 29 | |
| 14 | Surface water mapping for Watershed management using Geospatial technique | 2011 | 1 |
| 15 | 2010 | 178 | |
| 16 | 2010 | 61 | |
| 17 | Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimizationbreakdown → | 2009 | 1059 |
| 18 | 2009 | 143 | |
| 19 | Robust Face Recognition via Sparse Representationbreakdown → | 2009 | 6916 |
| 20 | 2008 | 107 |
About Arvind Ganesh
Arvind Ganesh is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Computational Mechanics, Bioengineering and Computer Graphics and Computer-Aided Design, having authored 43 papers that have together received 11.9k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (13 papers), Medical Image Segmentation Techniques (8 papers), Blind Source Separation Techniques (7 papers), Face and Expression Recognition (7 papers), Face recognition and analysis (5 papers), ZnO doping and properties (5 papers), Groundwater and Watershed Analysis (3 papers) and Image and Signal Denoising Methods (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (7.7k citations), Computational Mathematics (158 citations), Computational Mechanics (4.8k citations), Media Technology (2.0k citations) and Signal Processing (2.4k citations). Arvind Ganesh has collaborated with scholars based in India, United States and China. Frequent co-authors include John Wright, Shankar Sastry, Yi Ma, Yi Ma, Yigang Peng, Shankar Rao, Andrew Wagner, Wenli Xu, Zihan Zhou and Moshe Mishali. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information and Inference A Journal of the IMA, Sensors and Actuators B Chemical, Groundwater for Sustainable Development and ETRI Journal.
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.