Leon A. Gatys
- Computer Vision and Pattern Recognition top 0.2%
- Artificial Intelligence top 2%
- Computer Graphics and Computer-Aided Design top 0.5%
- Cognitive Neuroscience top 5%
- Media Technology top 1%
- Co-authors
- Matthias BethgeAlexander S. EckerThomas S. A. WallisEli ShechtmanAaron HertzmannMatthias KümmererAndreas S. ToliasEdgar Y. Walker
- Topics
- Visual Attention and Saliency Detection (6 papers)Generative Adversarial Networks and Image Synthesis (5 papers)Aesthetic Perception and Analysis (4 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionMedia Technology
- Partner nations
- GermanyUnited States
In The Last Decade
Leon A. Gatys
15 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Computer Vision and Pattern Recognition 3.1k
- Artificial Intelligence 676
- Computer Graphics and Computer-Aided Design 634
- Cognitive Neuroscience 539
- Media Technology 288
Countries citing papers authored by Leon A. Gatys
This map shows the geographic impact of Leon A. Gatys'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 Leon A. Gatys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leon A. Gatys more than expected).
Fields of papers citing papers by Leon A. Gatys
This network shows the impact of papers produced by Leon A. Gatys. 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 Leon A. Gatys. The network helps show where Leon A. Gatys may publish in the future.
Co-authorship network of co-authors of Leon A. Gatys
This figure shows the co-authorship network connecting the top 25 collaborators of Leon A. Gatys. A scholar is included among the top collaborators of Leon A. Gatys 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 Leon A. Gatys. Leon A. Gatys is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 29 | |
| 2 | 154 | |
| 3 | 2 | |
| 4 | 34 | |
| 5 | What does it take to generate natural textures | 11 |
| 6 | 276 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 37 | |
| 10 | 51 | |
| 11 | 182 | |
| 12 | 0 | |
| 13 | Image Style Transfer Using Convolutional Neural Networksbreakdown → | 3169 |
| 14 | Texture synthesis and the controlled generation of natural stimuli using convolutional neural networks | 43 |
| 15 | 6 | |
| 16 | 40 |
About Leon A. Gatys
Leon A. Gatys is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Cognitive Neuroscience, having authored 16 papers that have together received 4.0k indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Aesthetic Perception and Analysis (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (634 citations), Computer Vision and Pattern Recognition (3.1k citations) and Media Technology (288 citations). Leon A. Gatys has collaborated with scholars based in Germany and United States. Frequent co-authors include Matthias Bethge, Alexander S. Ecker, Thomas S. A. Wallis, Eli Shechtman, Aaron Hertzmann, Matthias Kümmerer, Andreas S. Tolias, Edgar Y. Walker, George H. Denfield and Santiago A. Cadena. Their work appears in journals such as Current Opinion in Neurobiology, eLife and PLoS Computational Biology.
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.