Samuel Albanie
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.5%
- Media Technology top 0.2%
- Radiology, Nuclear Medicine and Imaging top 1%
- Biomedical Engineering top 5%
- Co-authors
- Jie HuLi ShenGang SunEnhua WuAndrea VedaldiAndrew ZissermanArsha NagraniYang Liu
- Topics
- Multimodal Machine Learning Applications (14 papers)Domain Adaptation and Few-Shot Learning (9 papers)Human Pose and Action Recognition (8 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionArtificial Intelligence
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Samuel Albanie
28 papers receiving 8.9k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Computer Vision and Pattern Recognition 5.1k
- Artificial Intelligence 2.4k
- Media Technology 1.2k
- Radiology, Nuclear Medicine and Imaging 1.0k
- Biomedical Engineering 670
Countries citing papers authored by Samuel Albanie
This map shows the geographic impact of Samuel Albanie'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 Samuel Albanie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Albanie more than expected).
Fields of papers citing papers by Samuel Albanie
This network shows the impact of papers produced by Samuel Albanie. 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 Samuel Albanie. The network helps show where Samuel Albanie may publish in the future.
Co-authorship network of co-authors of Samuel Albanie
This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Albanie. A scholar is included among the top collaborators of Samuel Albanie 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 Samuel Albanie. Samuel Albanie 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 | 4 | |
| 3 | 5 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 13 | |
| 7 | 12 | |
| 8 | Crosslingual Generalization through Multitask Finetuningbreakdown → | 190 |
| 9 | 6 | |
| 10 | 36 | |
| 11 | 50 | |
| 12 | 8 | |
| 13 | 25 | |
| 14 | 1 | |
| 15 | 12 | |
| 16 | 8 | |
| 17 | Use What You Have: Video retrieval using representations from collaborative experts. | 13 |
| 18 | Squeeze-and-Excitation Networksbreakdown → | 8158 |
| 19 | Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks | 88 |
| 20 | 191 |
About Samuel Albanie
Samuel Albanie is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 30 papers that have together received 9.1k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (14 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Human Pose and Action Recognition (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.1k citations), Media Technology (1.2k citations) and Artificial Intelligence (2.4k citations). Samuel Albanie has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Jie Hu, Li Shen, Gang Sun, Enhua Wu, Andrea Vedaldi, Andrew Zisserman, Arsha Nagrani, Yang Liu, Gyungin Shin and Weidi Xie. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Artificial Intelligence.
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.