Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images
This map shows the geographic impact of Devis Tuia'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 Devis Tuia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Devis Tuia more than expected).
This network shows the impact of papers produced by Devis Tuia. 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 Devis Tuia. The network helps show where Devis Tuia may publish in the future.
Co-authorship network of co-authors of Devis Tuia
This figure shows the co-authorship network connecting the top 25 collaborators of Devis Tuia.
A scholar is included among the top collaborators of Devis Tuia 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 Devis Tuia. Devis Tuia is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tuia, Devis, Benjamin Kellenberger, Sara Beery, et al.. (2022). Perspectives in machine learning for wildlife conservation. Nature Communications. 13(1). 792–792.348 indexed citations breakdown →
Matasci, Giona, Lorenzo Bruzzone, Michele Volpi, Devis Tuia, & Mikhaïl Kanevski. (2013). Investigating the feature extraction framework for domain adaptation in remote sensing image classification. Infoscience (Ecole Polytechnique Fédérale de Lausanne).1 indexed citations
17.
Tuia, Devis, et al.. (2013). Multisource alignment of image manifolds. Infoscience (Ecole Polytechnique Fédérale de Lausanne).1 indexed citations
18.
Foresti, Loris, et al.. (2010). Time Series Input Selection using Multiple Kernel Learning. Socio-Environmental Systems Modeling.2 indexed citations
19.
Tuia, Devis, Dominique Fasbender, Patrick Bogaert, & Mikhaïl Kanevski. (2007). Bayesian data fusion for image enhancement : an application for thermal infrared ASTER sensors. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)).1 indexed citations
20.
Tuia, Devis & Mikhaïl Kanevski. (2006). Indoor radon data monitoring networks : Topology, fractality and validity domains. Socio-Environmental Systems Modeling.1 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.