Francesco Camastra

3.2k total citations · 1 hit paper
39 papers, 1.8k citations indexed

About

Francesco Camastra is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Francesco Camastra has authored 39 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 6 papers in Statistical and Nonlinear Physics. Recurrent topics in Francesco Camastra's work include Neural Networks and Applications (12 papers), Handwritten Text Recognition Techniques (8 papers) and Image Retrieval and Classification Techniques (7 papers). Francesco Camastra is often cited by papers focused on Neural Networks and Applications (12 papers), Handwritten Text Recognition Techniques (8 papers) and Image Retrieval and Classification Techniques (7 papers). Francesco Camastra collaborates with scholars based in Italy, Switzerland and United States. Francesco Camastra's co-authors include Alessandro Vinciarelli, Maurizio Filippone, Francesco Masulli, Stefano Rovetta, Alessandro Verri, Antonino Staiano, Angelo Ciaramella, Angelo Riccio, Valentina Rastelli and A.M. Colla and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Francesco Camastra

35 papers receiving 1.7k citations

Hit Papers

A survey of kernel and spectral methods for clustering 2007 2026 2013 2019 2007 100 200 300 400 500
What are hit papers?

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.

  1. A survey of kernel and spectral methods for clustering
    2007 554 citations Francesco Camastra et al. Pattern Recognition profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francesco Camastra Italy 19 900 779 234 223 144 39 1.8k
Maya R. Gupta United States 22 811 0.9× 618 0.8× 172 0.7× 275 1.2× 90 0.6× 93 1.9k
Francesco Masulli Italy 18 786 0.9× 491 0.6× 157 0.7× 234 1.0× 86 0.6× 113 1.5k
Ji‐Xiang Du China 27 1.1k 1.2× 1.3k 1.7× 247 1.1× 389 1.7× 137 1.0× 126 3.1k
Stefano Rovetta Italy 17 791 0.9× 670 0.9× 243 1.0× 256 1.1× 83 0.6× 103 1.6k
Fanhua Shang China 26 741 0.8× 1.2k 1.5× 349 1.5× 251 1.1× 98 0.7× 99 2.1k
Maurizio Filippone United Kingdom 20 934 1.0× 416 0.5× 125 0.5× 224 1.0× 125 0.9× 62 1.8k
Hujun Yin United Kingdom 27 948 1.1× 1.0k 1.3× 246 1.1× 273 1.2× 60 0.4× 164 2.5k
Timothy C. Havens United States 24 1.3k 1.5× 611 0.8× 234 1.0× 280 1.3× 245 1.7× 150 2.5k
Weixin Xie China 22 1.1k 1.3× 694 0.9× 282 1.2× 128 0.6× 139 1.0× 144 2.2k
Xiao‐Zhu Xie China 8 1.4k 1.5× 794 1.0× 270 1.2× 377 1.7× 187 1.3× 21 2.6k

Countries citing papers authored by Francesco Camastra

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Camastra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Camastra

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Camastra. A scholar is included among the top collaborators of Francesco Camastra 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 Francesco Camastra. Francesco Camastra 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.
Camastra, Francesco, et al.. (2025). Predicting ground-level nitrogen dioxide concentrations using the BaYesian attention-based deep neural network. Ecological Informatics. 87. 103097–103097.
2.
Camastra, Francesco, et al.. (2025). Spatio-temporal prediction using graph neural networks: A survey. Neurocomputing. 643. 130400–130400. 2 indexed citations
3.
4.
Camastra, Francesco, et al.. (2024). On the interpretability of fuzzy knowledge base systems. PeerJ Computer Science. 10. e2558–e2558. 1 indexed citations
5.
Camastra, Francesco, et al.. (2023). Deep Learning for Time Series Forecasting: Advances and Open Problems. Information. 14(11). 598–598. 60 indexed citations
6.
Giraldo, Jhony H., et al.. (2022). Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation. 2022 IEEE International Conference on Image Processing (ICIP). 9 indexed citations
7.
Camastra, Francesco, Maria Donata Di Taranto, & Antonino Staiano. (2015). Statistical and Computational Methods for Genetic Diseases: An Overview. Computational and Mathematical Methods in Medicine. 2015. 1–8. 14 indexed citations
8.
Camastra, Francesco, et al.. (2014). TÉRA: A tool for the environmental risk assessment of genetically modified plants. Ecological Informatics. 24. 186–193. 2 indexed citations
9.
Camastra, Francesco, et al.. (2012). Handy: A real-time three color glove-based gesture recognizer with learning vector quantization. Expert Systems with Applications. 39(12). 10489–10494. 18 indexed citations
10.
Camastra, Francesco. (2007). Image Processing: Principles and Applications [book review]. IEEE Transactions on Neural Networks. 18(2). 610–610. 9 indexed citations
11.
Camastra, Francesco & Alessandro Vinciarelli. (2007). Machine Learning for Audio, Image and Video Analysis: Theory and Applications (Advanced Information and Knowledge Processing). 13 indexed citations
12.
Camastra, Francesco, et al.. (2006). Offline Cursive Character Challenge: a New Benchmark for Machine Learning and Pattern Recognition Algorithms.. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 913–916. 37 indexed citations
13.
Camastra, Francesco, et al.. (2005). CURSIVE CHARACTER CHALLENGE: A NEW DATABASE FOR MACHINE LEARNING AND PATTERN RECOGNITION. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 3 indexed citations
14.
Camastra, Francesco & Alessandro Verri. (2005). A novel kernel method for clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 27(5). 801–805. 225 indexed citations
15.
Camastra, Francesco, et al.. (2004). ENHANCING CURSIVE WORD RECOGNITION PERFORMANCE BY THE INTEGRATION OF ALL THE AVAILABLE INFORMATION. Data Archiving and Networked Services (DANS). 1 indexed citations
16.
Camastra, Francesco. (2003). Data dimensionality estimation methods: a survey. Pattern Recognition. 36(12). 2945–2954. 179 indexed citations
17.
Camastra, Francesco & Alessandro Vinciarelli. (2002). Estimating the intrinsic dimension of data with a fractal-based method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 24(10). 1404–1407. 132 indexed citations
18.
Camastra, Francesco & Alessandro Vinciarelli. (1999). Isolated Cursive Character Recognition based on Neural Nets.. Künstliche Intell.. 13. 17–19. 2 indexed citations
19.
Camastra, Francesco & Alessandro Vinciarelli. (1999). Cursive character recognition based on neural nets. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam).
20.
Camastra, Francesco & A.M. Colla. (1999). Neural Short-Term Prediction Based on Dynamics Reconstruction. Neural Processing Letters. 9(1). 45–52. 17 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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