Udit Arora
Impact in
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- Face and Expression Recognition
- Face recognition and analysis
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Image and Video Stabilization
- Video Surveillance and Tracking Methods
- Signal Processing top 5%
- Biometric Identification and Security
Papers in
- Co-authors
- Pinaki ChakrabortyPrabhat MittalSavita YadavTanmoy ChakrabortyTushar SharmaPonnurangam KumaraguruMd Shad AkhtarPriyanka Priyanka
- Journals
- ACM Computing Surveys (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)Acta Paediatrica (1 paper)Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation (1 paper)Proceedings of the International AAAI Conference on Web and Social Media (2 papers)
- Partner nations
- IndiaUnited Kingdom
In The Last Decade
Udit Arora
9 papers receiving 452 citations
Peers
Comparison fields: 5 of 75
- Computer Vision and Pattern Recognition 394
- Signal Processing 125
- Media Technology 39
- Information Systems 40
- Computational Mathematics 1
Countries citing papers authored by Udit Arora
This map shows the geographic impact of Udit 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 Udit Arora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Udit Arora more than expected).
Fields of papers citing papers by Udit Arora
This network shows the impact of papers produced by Udit 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 Udit Arora. The network helps show where Udit Arora may publish in the future.
Co-authorship network
The 10 scholars most cited alongside Udit Arora, 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 | 2023 | 2 | |
| 2 | 2022 | 3 | |
| 3 | 2022 | 2 | |
| 4 | 2021 | 3 | |
| 5 | 2020 | 9 | |
| 6 | 2019 | 1 | |
| 7 | 2018 | 45 | |
| 8 | 2017 | 2 | |
| 9 | 2017 | 7 | |
| 10 | Face recognition: A literature survey | 2003 | 444 |
About Udit Arora
Udit Arora is a scholar working on Applied Psychology, Computer Science Applications, Computer Vision and Pattern Recognition, Information Systems and Health, having authored 10 papers that have together received 518 indexed citations. Recurring topics across this work include Spam and Phishing Detection (2 papers), Misinformation and Its Impacts (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Topic Modeling (2 papers), Retinal Imaging and Analysis (1 paper), Expert finding and Q&A systems (1 paper), Mental Health via Writing (1 paper) and Smart Parking Systems Research (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (394 citations), Signal Processing (125 citations), Media Technology (39 citations), Information Systems (40 citations) and Computational Mathematics (1 citation). Udit Arora has collaborated with scholars based in India and United Kingdom. Frequent co-authors include Pinaki Chakraborty, Prabhat Mittal, Savita Yadav, Tanmoy Chakraborty, Tushar Sharma, Ponnurangam Kumaraguru, Md Shad Akhtar, Priyanka Priyanka, Nidhi Goyal and Rajiv Ratn Shah. Their work appears in journals such as ACM Computing Surveys, ACM Transactions on Intelligent Systems and Technology, Acta Paediatrica, Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation and Proceedings of the International AAAI Conference on Web and Social Media.
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.