Yani Ioannou
- Computer Vision and Pattern Recognition top 5%
- Neurology top 5%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Biomedical Engineering
- Co-authors
- Antonio CriminisiMatthew A. BrownDarko ZikicDuncan RobertsonRoberto CipollaYann DauphinCem KeskinUtku Evci
- Topics
- Advanced Neural Network Applications (5 papers)Adversarial Robustness in Machine Learning (3 papers)Medical Image Segmentation Techniques (2 papers)
- Journals
- Child Care Health and DevelopmentCanadian Journal on Aging / La Revue canadienne du vieillissementInternational Conference on Learning Representations
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Yani Ioannou
9 papers receiving 211 citations
Peers
Comparison fields: 5 of 50
- Computer Vision and Pattern Recognition 155
- Neurology 138
- Artificial Intelligence 53
- Radiology, Nuclear Medicine and Imaging 40
- Biomedical Engineering 10
Countries citing papers authored by Yani Ioannou
This map shows the geographic impact of Yani Ioannou'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 Yani Ioannou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yani Ioannou more than expected).
Fields of papers citing papers by Yani Ioannou
This network shows the impact of papers produced by Yani Ioannou. 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 Yani Ioannou. The network helps show where Yani Ioannou may publish in the future.
Co-authorship network of co-authors of Yani Ioannou
This figure shows the co-authorship network connecting the top 25 collaborators of Yani Ioannou. A scholar is included among the top collaborators of Yani Ioannou 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 Yani Ioannou. Yani Ioannou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 11 | |
| 3 | 12 | |
| 4 | Deep Roots: Improving CNN Efficiency by Learning a Basis for Filter Dependencies | 0 |
| 5 | 1 | |
| 6 | Training Convolutional Neural Networks with Low-rank Filters for Efficient Image Classification | 4 |
| 7 | Decision Forests, Convolutional Networks and the Models in-Between Microsoft Research Technical Report 2015-58 | 1 |
| 8 | 17 | |
| 9 | Segmentation of Brain Tumor Tissues with Convolutional Neural Networks | 157 |
| 10 | 8 |
About Yani Ioannou
Yani Ioannou is a scholar working on Computer Vision and Pattern Recognition, Instrumentation and Physical Therapy, Sports Therapy and Rehabilitation, having authored 10 papers that have together received 223 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Adversarial Robustness in Machine Learning (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Neurology (138 citations), Computer Vision and Pattern Recognition (155 citations) and Instrumentation (6 citations). Yani Ioannou has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Antonio Criminisi, Matthew A. Brown, Darko Zikic, Duncan Robertson, Roberto Cipolla, Yann Dauphin, Cem Keskin, Utku Evci, Kathleen Michael and Douglas A. Caldwell. Their work appears in journals such as Child Care Health and Development, Canadian Journal on Aging / La Revue canadienne du vieillissement and International Conference on Learning Representations.
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.