Georgios Tzimiropoulos
About
In The Last Decade
Georgios Tzimiropoulos
87 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Computer Vision and Pattern Recognition 3.2k
- Signal Processing 883
- Experimental and Cognitive Psychology 520
- Artificial Intelligence 423
- Computational Mechanics 400
Countries citing papers authored by Georgios Tzimiropoulos
This map shows the geographic impact of Georgios Tzimiropoulos'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 Georgios Tzimiropoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georgios Tzimiropoulos more than expected).
Fields of papers citing papers by Georgios Tzimiropoulos
This network shows the impact of papers produced by Georgios Tzimiropoulos. 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 Georgios Tzimiropoulos. The network helps show where Georgios Tzimiropoulos may publish in the future.
Co-authorship network of co-authors of Georgios Tzimiropoulos
This figure shows the co-authorship network connecting the top 25 collaborators of Georgios Tzimiropoulos. A scholar is included among the top collaborators of Georgios Tzimiropoulos 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 Georgios Tzimiropoulos. Georgios Tzimiropoulos 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 | 1 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 29 | |
| 9 | Knowledge distillation via softmax regression representation learning | 32 |
| 10 | High-Capacity Expert Binary Networks | 16 |
| 11 | 24 | |
| 12 | 2 | |
| 13 | Unsupervised Learning of Object Landmarks via Self-Training Correspondence | 7 |
| 14 | XNOR-Net++: Improved binary neural networks. | 19 |
| 15 | 12 | |
| 16 | 246 | |
| 17 | 27 | |
| 18 | 23 | |
| 19 | 8 | |
| 20 | 300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge breakdown → | 686 |
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.