Antonio Rodrı́guez-Sánchez

983 total citations
36 papers, 578 citations indexed

About

Antonio Rodrı́guez-Sánchez is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Antonio Rodrı́guez-Sánchez has authored 36 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 14 papers in Cognitive Neuroscience and 12 papers in Artificial Intelligence. Recurrent topics in Antonio Rodrı́guez-Sánchez's work include Visual perception and processing mechanisms (11 papers), Neural dynamics and brain function (6 papers) and Robot Manipulation and Learning (6 papers). Antonio Rodrı́guez-Sánchez is often cited by papers focused on Visual perception and processing mechanisms (11 papers), Neural dynamics and brain function (6 papers) and Robot Manipulation and Learning (6 papers). Antonio Rodrı́guez-Sánchez collaborates with scholars based in Austria, Canada and Czechia. Antonio Rodrı́guez-Sánchez's co-authors include Justus Piater, John K. Tsotsos, Norbert Krüger, Laurenz Wiskott, Markus Lappe, Peter Janssen, Sinan Kalkan, Aleš Leonardis, Sebastian Stabinger and Zuzana Komínková Oplatková and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Brain Research.

In The Last Decade

Antonio Rodrı́guez-Sánchez

36 papers receiving 557 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Antonio Rodrı́guez-Sánchez Austria 11 285 185 119 94 51 36 578
Pradyut Kumar Biswal India 14 119 0.4× 207 1.1× 64 0.5× 128 1.4× 28 0.5× 58 519
Chaitanya Ekanadham United States 7 443 1.6× 152 0.8× 270 2.3× 56 0.6× 28 0.5× 13 851
Adam S. Charles United States 12 132 0.5× 168 0.9× 75 0.6× 157 1.7× 28 0.5× 38 638
Ziming Liu China 15 308 1.1× 108 0.6× 122 1.0× 90 1.0× 26 0.5× 42 828
Yikai Wang China 11 264 0.9× 121 0.7× 108 0.9× 30 0.3× 33 0.6× 21 544
Zongtan Zhou China 13 758 2.7× 128 0.7× 99 0.8× 227 2.4× 20 0.4× 26 986
Ziya Telatar Türkiye 10 171 0.6× 235 1.3× 135 1.1× 23 0.2× 36 0.7× 56 592
Masakazu Matsugu Japan 8 278 1.0× 63 0.3× 166 1.4× 30 0.3× 33 0.6× 18 601

Countries citing papers authored by Antonio Rodrı́guez-Sánchez

Since Specialization
Citations

This map shows the geographic impact of Antonio Rodrı́guez-Sánchez'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 Antonio Rodrı́guez-Sánchez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonio Rodrı́guez-Sánchez more than expected).

Fields of papers citing papers by Antonio Rodrı́guez-Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Antonio Rodrı́guez-Sánchez. 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 Antonio Rodrı́guez-Sánchez. The network helps show where Antonio Rodrı́guez-Sánchez may publish in the future.

Co-authorship network of co-authors of Antonio Rodrı́guez-Sánchez

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Rodrı́guez-Sánchez. A scholar is included among the top collaborators of Antonio Rodrı́guez-Sánchez 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 Antonio Rodrı́guez-Sánchez. Antonio Rodrı́guez-Sánchez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cesari, Matteo, Ambra Stefani, Abubaker Ibrahim, et al.. (2024). Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disorder. Brain Sciences. 14(9). 871–871. 6 indexed citations
2.
Saveriano, Matteo, et al.. (2023). Continual learning from demonstration of robotics skills. Robotics and Autonomous Systems. 165. 104427–104427. 12 indexed citations
3.
Stabinger, Sebastian, et al.. (2022). Improving 3D Point Cloud Reconstruction with Dynamic Tree-Structured Capsules. abs/1710.09829. 1–6. 1 indexed citations
4.
Rodrı́guez-Sánchez, Antonio, et al.. (2022). Affordance detection with Dynamic-Tree Capsule Networks. abs/1710.09829. 873–879. 1 indexed citations
5.
Stabinger, Sebastian, et al.. (2022). Greedy-layer pruning: Speeding up transformer models for natural language processing. Pattern Recognition Letters. 157. 76–82. 19 indexed citations
6.
Stabinger, Sebastian, et al.. (2021). Neural networks / Arguments for the unsuitability of convolutional neural networks for non-local tasks. Digital Library of the University of Innsbruck (University of Innsbruck). 5 indexed citations
7.
Stabinger, Sebastian, et al.. (2021). Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks. 37. 256–265. 5 indexed citations
8.
Stabinger, Sebastian, et al.. (2021). conflicting_bundle.py—A python module to identify problematic layers in deep neural networks. Software Impacts. 7. 100053–100053. 1 indexed citations
9.
Oplatková, Zuzana Komínková, et al.. (2020). Improving CT Image Tumor Segmentation Through Deep Supervision and Attentional Gates. Frontiers in Robotics and AI. 7. 106–106. 43 indexed citations
10.
Rodrı́guez-Sánchez, Antonio, et al.. (2017). Can Affordances Guide Object Decomposition into Semantically Meaningful Parts?. 36. 82–90. 5 indexed citations
11.
Rodrı́guez-Sánchez, Antonio, et al.. (2015). Diversity priors for learning early visual features. Frontiers in Computational Neuroscience. 9. 104–104. 9 indexed citations
12.
Azzopardi, George, Antonio Rodrı́guez-Sánchez, Justus Piater, & Nicolai Petkov. (2014). A Push-Pull CORF Model of a Simple Cell with Antiphase Inhibition Improves SNR and Contour Detection. PLoS ONE. 9(7). e98424–e98424. 31 indexed citations
13.
Porras-Amores, César, et al.. (2014). Assessing the potential use of strategies independent from the architectural design to achieve efficient ventilation: A Spanish case study. Building Services Engineering Research and Technology. 35(5). 529–542. 7 indexed citations
14.
Krüger, Norbert, Peter Janssen, Sinan Kalkan, et al.. (2013). Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(8). 1847–1871. 243 indexed citations
15.
Rodrı́guez-Sánchez, Antonio & John K. Tsotsos. (2012). The Roles of Endstopped and Curvature Tuned Computations in a Hierarchical Representation of 2D Shape. PLoS ONE. 7(8). e42058–e42058. 30 indexed citations
16.
Rodrı́guez-Sánchez, Antonio & John K. Tsotsos. (2011). The importance of intermediate representations for the modeling of 2D shape detection: Endstopping and curvature tuned computations. 2. 4321–4326. 9 indexed citations
17.
Rodrı́guez-Sánchez, Antonio, John K. Tsotsos, Stefan Treue, & Julio Martínez-Trujillo. (2009). Comparing neuronal and behavioral thresholds for spiral motion discrimination. Neuroreport. 20(18). 1619–1624. 2 indexed citations
18.
Tsotsos, John K., et al.. (2008). The different stages of visual recognition need different attentional binding strategies. Brain Research. 1225. 119–132. 39 indexed citations
19.
Rodrı́guez-Sánchez, Antonio, et al.. (2008). VISUAL FEATURE BINDING WITHIN THE SELECTIVE TUNING ATTENTION FRAMEWORK. International Journal of Pattern Recognition and Artificial Intelligence. 22(5). 861–881. 4 indexed citations
20.
Rodrı́guez-Sánchez, Antonio, et al.. (2007). ATTENTION AND VISUAL SEARCH. International Journal of Neural Systems. 17(4). 275–288. 22 indexed citations

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.

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