Germana Landi

46 papers and 409 indexed citations i.

About

Germana Landi is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Mathematical Physics. According to data from OpenAlex, Germana Landi has authored 46 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 18 papers in Computational Mechanics and 18 papers in Mathematical Physics. Recurrent topics in Germana Landi’s work include Inverse Problems in Mathematical Physics and Imaging (18 papers), Sparse and Compressive Sensing Techniques (17 papers) and Image and Signal Denoising Methods (17 papers). Germana Landi is often cited by papers focused on Inverse Problems in Mathematical Physics and Imaging (18 papers), Sparse and Compressive Sensing Techniques (17 papers) and Image and Signal Denoising Methods (17 papers). Germana Landi collaborates with scholars based in Italy and United States. Germana Landi's co-authors include Elena Loli Piccolomini, Fabiana Zama, Villiam Bortolotti, Paola Fantazzini, Daniela di Serafino, R. James Brown, Daniela Calvetti, Fiorella Sgallari, Lothar Reichel and Antonellá Tosti and has published in prestigious journals such as Microporous and Mesoporous Materials, SIAM Journal on Scientific Computing and Computers & Mathematics with Applications.

In The Last Decade

Co-authorship network of co-authors of Germana Landi i

Fields of papers citing papers by Germana Landi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Germana Landi. 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 Germana Landi. The network helps show where Germana Landi may publish in the future.

Countries citing papers authored by Germana Landi

Since Specialization
Citations

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

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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