Alykhan Tejani
Impact in
- Computer Vision and Pattern Recognition top 0.05%
- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
- Advanced Vision and Imaging
- Generative Adversarial Networks and Image Synthesis
- Image Enhancement Techniques
- Digital Media Forensic Detection
- Media Technology top 0.05%
- Image Processing Techniques and Applications
- Advanced Image Fusion Techniques
Papers in
-
- Human Pose and Action Recognition 2
- Multimodal Machine Learning Applications 1
- Co-authors
- Wenzhe Shi (8 shared papers)Ferenc Huszár (4 shared papers)Lucas Theis (2 shared papers)José Caballero (1 shared paper)Alejandro Acosta (1 shared paper)Andrew P. Aitken (1 shared paper)Zehan Wang (1 shared paper)Andrew Cunningham (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesItalyUnited Kingdom
In The Last Decade
Alykhan Tejani
11 papers receiving 7.9k citations
Alykhan Tejani's Hit Papers
Peers
Comparison fields: 5 of 156
- Computer Vision and Pattern Recognition 6.5k
- Media Technology 2.7k
- Computer Graphics and Computer-Aided Design 213
- Human-Computer Interaction 251
- Biophysics 156
Countries citing papers authored by Alykhan Tejani
This map shows the geographic impact of Alykhan Tejani'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 Alykhan Tejani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alykhan Tejani more than expected).
Fields of papers citing papers by Alykhan Tejani
This network shows the impact of papers produced by Alykhan Tejani. 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 Alykhan Tejani. The network helps show where Alykhan Tejani may publish in the future.
Co-authors
The 25 scholars most cited alongside Alykhan Tejani, 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 | Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network Hit paper breakdown → | 2017 | 7710 |
| 2 | 2014 | 240 | |
| 3 | 2017 | 44 | |
| 4 | 2016 | 39 | |
| 5 | 2019 | 32 | |
| 6 | 2020 | 25 | |
| 7 | 2020 | 17 | |
| 8 | 2020 | 8 | |
| 9 | 2021 | 8 | |
| 10 | 2021 | 4 | |
| 11 | Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline | 2020 | 2 |
About Alykhan Tejani
Alykhan Tejani is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Management Science and Operations Research and Computer Science Applications, having authored 11 papers that have together received 8.1k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (3 papers), Hand Gesture Recognition Systems (2 papers), Human Pose and Action Recognition (2 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Advanced Bandit Algorithms Research (2 papers), Spam and Phishing Detection (1 paper), Multimodal Machine Learning Applications (1 paper) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (6.5k citations), Media Technology (2.7k citations), Computer Graphics and Computer-Aided Design (213 citations), Human-Computer Interaction (251 citations) and Biophysics (156 citations). Alykhan Tejani has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Wenzhe Shi, Ferenc Huszár, Lucas Theis, José Caballero, Alejandro Acosta, Andrew P. Aitken, Zehan Wang, Andrew Cunningham, Johannes Totz and Christian Ledig. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence 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.