Filippo Nencini

4.0k total citations · 4 hit papers
38 papers, 3.3k citations indexed

About

Filippo Nencini is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Filippo Nencini has authored 38 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Media Technology, 28 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in Filippo Nencini's work include Remote-Sensing Image Classification (32 papers), Advanced Image Fusion Techniques (31 papers) and Image and Signal Denoising Methods (22 papers). Filippo Nencini is often cited by papers focused on Remote-Sensing Image Classification (32 papers), Advanced Image Fusion Techniques (31 papers) and Image and Signal Denoising Methods (22 papers). Filippo Nencini collaborates with scholars based in Italy and United States. Filippo Nencini's co-authors include Andrea Garzelli, Luciano Alparone, Stefano Baronti, Luca Capobianco, Bruno Aiazzi, Massimo Selva, Lorenzo Bruzzone, Silvia Marchesi, Francesca Bovolo and Andrea Abrardo and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Pattern Recognition and International Journal of Remote Sensing.

In The Last Decade

Filippo Nencini

38 papers receiving 3.2k citations

Hit Papers

Multispectral and Panchromatic Data Fusion Assessment Wit... 2004 2026 2011 2018 2008 2006 2004 2007 200 400 600

Peers

Filippo Nencini
O. Fors Spain
Qi Wei France
Le Sun China
Filippo Nencini
Citations per year, relative to Filippo Nencini Filippo Nencini (= 1×) peers Massimo Selva

Countries citing papers authored by Filippo Nencini

Since Specialization
Citations

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

Fields of papers citing papers by Filippo Nencini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Filippo Nencini

This figure shows the co-authorship network connecting the top 25 collaborators of Filippo Nencini. A scholar is included among the top collaborators of Filippo Nencini 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 Filippo Nencini. Filippo Nencini 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.
Garzelli, Andrea, Luca Capobianco, & Filippo Nencini. (2009). On the effects of pan-sharpening to target detection. Use Siena air (University of Siena). 66. II–136. 7 indexed citations
2.
Garzelli, Andrea & Filippo Nencini. (2009). Hypercomplex Quality Assessment of Multi/Hyperspectral Images. IEEE Geoscience and Remote Sensing Letters. 6(4). 662–665. 291 indexed citations
3.
Bovolo, Francesca, Lorenzo Bruzzone, Luca Capobianco, et al.. (2009). Analysis of the Effects of Pansharpening in Change Detection on VHR Images. IEEE Geoscience and Remote Sensing Letters. 7(1). 53–57. 103 indexed citations
4.
Abrardo, Andrea, Mauro Barni, Andrea Garzelli, et al.. (2008). Low-complexity, secure and error-resilient hyperspectral image compression. PORTO Publications Open Repository TOrino (Politecnico di Torino). 1 indexed citations
5.
Nencini, Filippo, Luca Capobianco, & Andrea Garzelli. (2008). Weighted Least Squares Pan-Sharpening of Very High Resolution Multispectral Images. Use Siena air (University of Siena). V – 65. 6 indexed citations
6.
Alparone, Luciano, Bruno Aiazzi, Stefano Baronti, et al.. (2008). Multispectral and Panchromatic Data Fusion Assessment Without Reference. Photogrammetric Engineering & Remote Sensing. 74(2). 193–200. 685 indexed citations breakdown →
7.
Abrardo, Andrea, Mauro Barni, Andrea Garzelli, et al.. (2008). Low-complexity and error-resilient hyperspectral image compression based on distributed source coding. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7109. 71090V–71090V. 1 indexed citations
8.
Barni, Mauro, et al.. (2007). Low-complexity lossless compression of hyperspectral images using scalar coset codes. PORTO Publications Open Repository TOrino (Politecnico di Torino). 1 indexed citations
9.
Capobianco, Luca, et al.. (2007). Introducing training and parameter tuning for KOSP classification of hyperspectral images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6748. 67480B–67480B. 2 indexed citations
10.
Garzelli, Andrea & Filippo Nencini. (2007). A genetic approach to Pan-sharpening of multispectral images. Use Siena air (University of Siena). 1 indexed citations
11.
Garzelli, Andrea, Filippo Nencini, & Luca Capobianco. (2007). Optimal MMSE Pan Sharpening of Very High Resolution Multispectral Images. IEEE Transactions on Geoscience and Remote Sensing. 46(1). 228–236. 472 indexed citations breakdown →
12.
Aiazzi, Bruno, Stefano Baronti, Luciano Alparone, Andrea Garzelli, & Filippo Nencini. (2006). Information-Theoretic Assessment of Fusion of Multispectral and Panchromatic Images. Florence Research (University of Florence). 9. 1–5. 9 indexed citations
13.
Garzelli, Andrea & Filippo Nencini. (2006). Fusion of Panchromatic and Multispectral Images by Genetic Algorithms. Use Siena air (University of Siena). 40 indexed citations
14.
Garzelli, Andrea & Filippo Nencini. (2006). PAN‐sharpening of very high resolution multispectral images using genetic algorithms. International Journal of Remote Sensing. 27(15). 3273–3292. 46 indexed citations
15.
Alparone, Luciano, Bruno Aiazzi, Stefano Baronti, Andrea Garzelli, & Filippo Nencini. (2006). A New Method for MS + Pan Image Fusion Assessment Without Reference. Florence Research (University of Florence). 63. 3802–3805. 10 indexed citations
16.
Garzelli, Andrea, Filippo Nencini, Luciano Alparone, & Stefano Baronti. (2005). Multiresolution fusion of multispectral and panchromatic images through the curvelet transform. Florence Research (University of Florence). 4. 2838–2841. 24 indexed citations
17.
Alparone, Luciano, Luca Facheris, Stefano Baronti, Andrea Garzelli, & Filippo Nencini. (2004). Fusion of Multispectral and SAR images by Intensity Modulation. Florence Research (University of Florence). 2. 637–643. 34 indexed citations
18.
Alparone, Luciano, Stefano Baronti, Andrea Garzelli, & Filippo Nencini. (2004). A Global Quality Measurement of Pan-Sharpened Multispectral Imagery. IEEE Geoscience and Remote Sensing Letters. 1(4). 313–317. 494 indexed citations breakdown →
19.
Alparone, Luciano, Stefano Baronti, Andrea Garzelli, & Filippo Nencini. (2004). Landsat ETM+ and SAR image fusion based on generalized intensity Modulation. IEEE Transactions on Geoscience and Remote Sensing. 42(12). 2832–2839. 105 indexed citations
20.
Garzelli, Andrea & Filippo Nencini. (2004). Interband structure modeling for Pan-sharpening of very high-resolution multispectral images. Information Fusion. 6(3). 213–224. 75 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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