Publications

Journals

1. V.M. Scarrica, C. Panariello, A. Ferone, A. Staiano, A Hybrid Approach to Real-Time Multi-Target Tracking, Neural Computing and Applications, 36 (17), pp. 10055-10066, 2024

2. A. Lanzoni, A. Staiano, A. Masetti, A. Burgio, Evaluation of lethal and sublethal effects of laminarin on the green peach aphid, Myzus persicae, under extended laboratory conditions, Entomologia Experimentalis et Applicata, https://doi.org/10.1111/eea.13410, 2024

3. V. M. Scarrica, P.P.C. Aucelli, C. Cagnazzo, A. Casolaro, P. Fiore, M. La Salandra, A. Rizzo, G. Scardino, G. Scicchitano, A. Staiano, A novel beach litter analysis system based on UAV images and Convolutional Neural Networks, Ecological Informatics, Vol. 72, 2022.

4. F. Camastra, V. Capone, A. Ciaramella, A. Riccio, A. Staiano, Prediction of Environmental Missing Data Time Series by Support Vector Machine Regression and Correlation Dimension Estimation, Environmental Modelling and Software, vol. 150, 2022.

5. A. Lanzoni, G. Burgio, F. Camastra, A. Ciaramella, A. Staiano, V. Bregola, S. Bosi, G. Dinelli, Assessing the effects of Bt Maize on the non-target pest Rhopalosiphum maidis by demographic and life-history measurement endpoints, Bulletin of Entomological Research, Vol. 112, Issue 1, pp. 29-43, 2022

6. L.H. Son, A. Ciaramella, D.T. Thu, A. Staiano, T. M. Tuan, P. Van Hai,  Predictive reliability and validity of hospital cost analysis with dynamic neural network and genetic algorithm. NEURAL COMPUTING & APPLICATIONS, 32, 2020

7. A. Ciaramella, D. Nardone, A. Staiano, Data Integration by Fuzzy Similarity-based Hierarchical Clustering, BMC Bioinformatics 21, Article number 350, 2020

8. D. Nardone, A. Ciaramella, A. Staiano, A Sparse-Modeling Based Approach for Class Specific Feature Selection, PeerJ Computer Science, 5:e237, https://doi.org/10.7717/peerj-cs.237, 2019

9. A. Ciaramella, A. Staiano, On the Role of Clustering and Visualization Techniques in Gene Microarray Data, Algorithms, 12 (6):123, 2019

10. F. Recknagel, A. Staiano, Analysis and synthesis of ecological data by machine learning, Ecological Informatics, Article number 10097, 2019

11. E. Chianese, F. Camastra, A. Ciaramella, T.C. Landi, A. Staiano, A. Riccio, Spatio-temporal learning in predicting ambient particulate matter concentration by multi-layer perceptron, Ecological Informatics, Vol. 49, pp. 54-61, 2019

12. F. Camastra, F. Esposito, A. Staiano, Linear SVM-based recognition of elementary juggling movements using correlation dimension of Euler Angles of a single arm, Neural Computing and Applications, 29 (11), 1005-1013, 2018.

13. F. Camastra, A. Staiano, Intrinsic dimension estimation: Advances and open problems, Information Sciences, 328, pp. 26-42, 2016.

14. F. Camastra, M. D. Di Taranto, A. Staiano, Statistical and Computational Methods for Genetic Diseases: An Overview, Computational and Mathematical Methods in Medicine, vol. 2015 (Special Issue on Advances in Computational Methods for Genetic Diseases, F. Camastra, R. Amato, M.D. Di Taranto, A. Staiano Eds), Article ID 954598, 2015. doi:10.1155/2015/954598

15. M.D. Di Taranto, A. Staiano, M.N. D’Agostino, A. D’Angelo, E. Bloise, A. Morgante, G. Marotta, M. Gentile, P. Rubba, G. Fortunato, Association of USF1 and APOA5 polymorphisms with Familial Combined Hyperlipidemia in an Italian population, Molecular and Cellular Probes, 29 (1), pp. 19-24, 2015.

16. F. Camastra, A. Ciaramella, V. Govannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace, A Fuzzy Decision System for Genetically Modified Plant Environmental Risk Assessment using Mamdani Inference, Expert Systems with Applications, 42(3), pp. 1710-1716, 2015

17. F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace, TÉRA: A Tool for the Environmental Risk Assessment of Genetically Modified Plants, Ecological Informatics, 21, 186-193, 2014

18. F. Camastra, A. Ciaramella, A. Staiano, A note on some mathematical models on the effects of Bt-maize exposure, Environmental and Ecological Statistics, 21, 477-485, 2014

19. F. Camastra, A. Ciaramella, A. Staiano, Machine Learning and Soft Computing for ICT security: an overview of current trends, Journal of Ambient Intelligence and Humanized Computing, 4, 235-247, 2013

20. G. Calcagno, A. Staiano, G. Fortunato, V. Brescia-Morra, E. Salvatore, R. Liguori, S. Capone, A. Filla, G. Longo, L. Sacchetti, A multilayer perceptron neural network-based approach for the identification of responsiveness to interferon therapy in multiple sclerosis patients, Information Sciences, 180 (21), 4153-4163, 2010 

21. A. Petrosino, A. Staiano, Fuzzy Modeling for Data Cleaning in Sensor Networks, International Journal of Hybrid Intelligent Systems, IOS Press, 5(3), 143-151, 2008 

22. F. Napolitano, G. Raiconi, R. Tagliaferri, A. Ciaramella, A. Staiano, G. Miele, Clustering and Visualization Approaches for Human Cell Cycle Gene Expression Analysis, International Journal of Approximate Reasoning,    47(1), 70-84, 2008 

23. R. D’Abrusco, A. Staiano, G. Longo, E. De Filippis, M. Brescia, M. Paolillo, Mining the SDSS archive. I. Photometric redshift in the nearby universe, The Astrophysical Journal, 663, 752, 2007

24. R. D’Abrusco, A. Staiano, G. Longo, E. De Filippis, M. Brescia, M. Paolillo, Steps towards a map of the nearby universe, Nuclear Physics B - Proceedings Supplements, Volume 168, pp. 299-301, 2007 

25. R. Amato, A. Ciaramella, A. Staiano, R. Tagliaferri et al., A multi-step approach to time series analysis and gene expression clustering, Bioinformatics Vol. 22, N. 5, pp. 589-596, 2006 

26. A. Staiano, R. Tagliaferri, W. Pedrycz, Improving RBF Networks Performance in Regression Tasks by Means of a Supervised Fuzzy Clustering, Neurocomputing, 69:1570-1581, 2006

27. A. Staiano, R. Tagliaferri, G. Longo et al., Novel Techniques for Microarray Data Analysis: Probabilistic Principal Surfaces and Competitive Evolution on Data, Journal of Computational and Theoretical Nanoscience, Special Issue on Computational Intelligence for Molecular Biology and Bioinformatics, Volume 2, N. 4, pp. 514-523, 2005 

28. R. Tagliaferri R., G. Longo, A. Staiano et al., Applications of Neural Networks in Astronomy and Astroparticle Physics, invited review on “Recent Research Developments in Astronomy and Astrophysics” by Research Signpost, Vol. 2, pp.27-58, 2005 

29. R. Tagliaferri R., G. Longo, A. Staiano et al., Neural Networks in Astronomy, in Neural Networks. Special Issue su Neural networks for analysis of complex scientific data: Astronomy and Geosciences, R. Tagliaferri, G. Longo, D’Argenio B. (Eds), vol. 16 (3-4), 2003

30. A. Di Nola, V. Loia, A. Staiano, An Evolutionary Approach to Spatial Fuzzy Clustering, Fuzzy Optimization and Decision Making, 1, 195-219, 2002 

31. V. Loia, S. Sessa, A. Staiano, R. Tagliaferri, Merging Fuzzy Logic, Neural Networks and Genetic Computation in the Design of a Decision-Support System, International Journal of Intelligent Systems, John Wiley and Sons, Inc., Vol. 15, 575-594, 2000

Conferences

1. A. Sozio, A. Rizzo, V.M. Scarrica, P.P.C. Aucelli, G. Anfuso, G. Barracane, L.A. Dimuccio, R. Ferreira, M. La Salandra, A. Staiano, M.P. Tarantino, G. Scicchitano, An Innovative SAM-ViT-based tool for the automatic detection of litter items on sandy beaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8657, https://doi.org/10.5194/egusphere-egu24-8657, 2024.

2. A. Sozio, V. M. Scarrica, P. P. C. Aucelli, G. Scicchitano, A. Staiano and A. Rizzo, "Comparing Meanshift/SVM and Mask-RCNN algorithms for beach litter detection on UAVs images," 2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea), La Valletta, Malta, pp. 483-487, 2023

3. A. Ferone, M. Lazzaro, V.M. Scarrica, A. Ciaramella, A. Staiano, A Synthetic Dataset for Learning Optical Flow in Underwater Environment. In: Esposito, A., Faundez-Zanuy, M., Morabito, F.C., Pasero, E. (eds) Applications of Artificial Intelligence and Neural Systems to Data Science. Smart Innovation, Systems and Technologies, vol 360. Springer, Singapore, 2023

4. J. H. Giraldo, T. Bouwmans, V. Scarrica, A. Staiano, F. Camastra, Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation, IEEE ICIP 2022, Bordeaux, France

5. V. Scarrica, A. Rizzo, P. Aucelli, A. Casolaro, A. Morelli, G. Scardino, G. Scicchitano, A. Staiano, Convolutional Neural Networks for Beach litter monitoring from UAV images, 16th Littoral22, Costa de Caparica, Portugal

6. A. Ferone, M. Lazzaro, V. Scarrica, A. Ciaramella, A. Staiano, A Synthetic Dataset for Learning Optical Flow in Underwater Environment, WIRN 2022, Vietri sul Mare, Italy

7. F. Camastra, V. Capone, A. Ciaramella, T.C. Landi, A. Riccio, A. Staiano, Environmental Time Series Prediction with Missing Data by Machine Learning and Dynamics Reconstruction, LNCS, Vol. 12666, pp. 26-33, Springer, 2021

8. A. Ciaramella, D. Nardone, A. Staiano, G. Vettigli G., Audio content-based framework for emotional music recognition. In: Gloria Philips - Wren Anna Esposito Lakhmi C. Jain. Intelligent Systems Reference Library. INTELLIGENT SYSTEMS REFERENCE LIBRARY, vol. 189, p. 277-292, Springer, ISBN: 978-3-030-51869-1, 2020

9. A. Ciaramella, D. Nardone, A. Staiano, Blind Source Separation Using Dictionary Learning in Wireless Sensor Network Scenario. In: Esposito A. Faundez-Zanuy M. Morabito F. Pasero E.. Smart Innovation, Systems and Technologies. SMART INNOVATION, SYSTEMS AND TECHNOLOGIES, vol. 151, p. 119-131, Springer Science and Business Media Deutschland GmbH, ISBN: 978-981-13-8949-8, 2020

10. A. Ciaramella, D. Nardone, A. Staiano, Compressive Sensing and Hierarchical Clustering for Microarray Data with Missing Values. In: Raposo M.Ribeiro P.Serio S.Staiano A.Ciaramella A., LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, vol. 11925, p. 3-10, Springer, ISBN: 978-3-030-34584-6, 2020

11. F. Camastra, A. Ciaramella, A. Maratea, L.H. Son, A. Staiano A., Semantic Maps for Knowledge Management of Web and Social Information. In: G. Acampora W. Pedrycz A.V. Vasilakos A. Vitiello. (a cura di): G. Acampora W. Pedrycz A.V. Vasilakos A. Vitiello, Studies in Computational Intelligence. STUDIES IN COMPUTATIONAL INTELLIGENCE, vol. 837, p. 39-51, Springer Verlag, ISBN: 978-3-030-23758-5, 2020

12. D. Davino, F. Camastra, A. Ciaramella, A. Staiano A, Spam Detection by Machine Learning-Based Content Analysis. In: Anna Esposito Marcos Faundez-Zanuy Francesco Carlo Morabito Eros Pasero. Smart Innovation, Systems and Technologies. SMART INNOVATION, SYSTEMS AND TECHNOLOGIES, vol. 184, p. 415-422, Springer, ISBN: 978-981-15-5092-8, 2020

13. M. Iannicelli, D. Nardone, A. Ciaramella, A. Staiano, Content-based music agglomeration by sparse modeling and convolved independent component analysis. In: Anna Esposito Marcos Faundez-Zanuy Francesco Carlo Morabito Eros Pasero. Smart Innovation, Systems and Technologies. SMART INNOVATION, SYSTEMS AND TECHNOLOGIES, vol. 103, p. 87-96, Springer Science and Business Media Deutschland GmbH, ISBN: 978-3-319-95094-5, 2019

14. F. Camastra, A. Ciaramella, L.H. Son, A. Riccio, A. Staiano, Fuzzy Similarity-Based Hierarchical Clustering for Atmospheric Pollutants Prediction. In: R. Fullér S. Giove F. Masulli. LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, vol. 11291, p. 123-133, Springer Verlag, ISBN: 9783030125431, 2019

15. A. Lanzoni, F. Camastra, A. Ciaramella, A. Staiano, G. Burgio, Modeling Green Peach Aphid populations exposed to elicitors inducing plant resistance on peach, ICEI 2018, September 24-28, Jena, Germany, 2018

16. A. Ciaramella, D. Nardone, A. Staiano, Compressive Sensing and Hierarchical Clustering for Microarray Data with Missing Values, CIBB 2018, September 6-8, Costa De Caparica, Lisbon, Portugal, 2018

17. F. Camastra, A. Ciaramella, A. Riccio, S. Le Hoang, A. Staiano, Fuzzy Similarity-based Hierarchical Clustering for Atmospheric Pollutants Prediction, WILF 2018, September 6-7, Genova, Italy, 2018

18. A. Ciaramella, D. Nardone, A. Staiano, Blind source separation using dictionary learning in wireless sensor network scenario, WIRN 2018, June 13-15, Vietri sul Mare (Sa), Italy, 2018

19. F. Camastra, F. Esposito, A. Staiano, Correlation Dimension-Based Recognition of Simple Juggling Movements, Multidisciplinary Approaches to Neural Computing. Smart Innovation, Systems and Technologies, vol 69, pp. 77-84, Springer, 2018

20. F. Camastra, A. Ciaramella, A. Staiano, On the Estimation of Pollen Density on Non-target Lepidoptera Food Plant Leaves in Bt-Maize Exposure Models: Open Problems and Possible Neural Network-Based Solutions, In: Lintas A., Rovetta S., Verschure P., Villa A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2017. ICANN 2017. Lecture Notes in Computer Science, vol 10613. pp. 407-414, Springer, 2017

21. A. Ciaramella, A. Staiano, G. Cervone, S. Alessandrini, A bayesian-based neural network model for solar photovoltaic power forecasting, Advances in Neural Networks. Smart Innovation, Systems and Technologies, vol 54, pp. 169-177, Springer, 2016

22. A. Staiano, F. Inneguale, An RBF neural network-based system for home smart metering, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017

23. F. Camastra, A. Ciaramella, A. Placitelli, A. Staiano, Machine Learning-based Web Documents Categorization by Semantic Graphs, In: Bassis S., Esposito A., Morabito F. (eds) Advances in Neural Networks: Computational and Theoretical Issues. Smart Innovation, Systems and Technologies, vol 37, pp. 75-82, Springer, 2015

24. F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace, Environmental Risk Assessment of Genetically Modified Organisms by a Fuzzy Decision Support System, in  A. Petrosino, L. Maddalena, P. Pala (Eds), New Trends in Image Analysis and Processing – ICIAP 2013. Lecture Notes In Computer Science, vol. 8158, 2013

25. A. Staiano, M.D. Di Taranto, E. Bloise, M.N. D'Agostino, A. D'Angelo, G. Marotta, M. Gentile, F. Jossa, A. Iannuzzi, P. Rubba, G. Fortunato, Investigation of Single Nucleotide Polymorphisms associated to Familial Combined Hyperlipidemia with Random Forests, in B. Apolloni, S. Bassis, A. Esposito, F.C. Morabito, Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol. 19, p. 169-178, 2013

26. A. Staiano, F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, S. Sposato, G. Staiano, A. Starace, Rule Learning in a Fuzzy Decision Support System for the Environmental Risk Assessment of GMOs, in Masulli, Pasi, Yager(Eds.), Fuzzy Logic and Applications. Lecture Notes In Computer Science, vol. 8256, Springer International Publishing Switzerland, 2013

27. A. Petrosino, A. Staiano, A Neural Based WSN Mote Trajectory Reconstruction for Mining Periodic Patterns, Proceeding WIRN 2008, Frontiers in Artificial Intelligence and Applications - New Directions in Neural Networks, Apolloni, Bassis, Marinaro (Eds), Vol. 193, pp. 3-11, 2009 

28. A. Petrosino, A. Staiano, A Neuro-Fuzzy Approach for Sensor Network Data Cleaning, in Apolloni et al. (Eds): KES-WIRN 2007, LNAI 4694, pp. 140-147, Springer-Verlag, 2007

29. R. D’Abrusco, G. Longo, M. Brescia, E. De Filippis, M. Paolillo, A. Staiano, R. Tagliaferri, Mining the Structure of the Nearby Universe, in Modeling and Simulation in Science: 6th International Workshop on Data Analysis in Astronomy, Di Gesu` , Lo Bosco, Maccarone Eds., World Scientific, 2007

30. A. Ciaramella, F. Iorio, F. Napolitano, G. Raiconi, G. Miele, A. Staiano, R. Tagliaferri, Data Visualization and Clustering: an application to gene expression data, in Modeling and Simulation in Science: 6th International Workshop on Data Analysis in Astronomy, Di Gesu` , Lo Bosco, Maccarone Eds., World Scientific, 2007

31. R. Amato, A. Ciaramella, A. Staiano, R. Tagliaferri, G. Longo, et al., NEC for Gene Expression Analysis, LNCS Vol. 3849/2006, pp. 246-251. Fuzzy Logic and Applications: 6th International Workshop, WILF 2005

32. A. Ciaramella, A. Staiano, R. Tagliaferri, G. Longo, NEC: an Hierarchical Agglomerative Clustering based on Fischer and Negentropy Information, LNCS Vol. 3931/2006, pp. 49-56. WIRN-NAIS 2005

33. A. Staiano, A. Ciaramella, R. Tagliaferri et al., Visualization, Clustering and Classification of Multidimensional Astronomical Data, IEEE Seventh International Workshop on Computer Architecture for Machine Perception (CAMP), pp. 141-146, 2005

34. A. Staiano, A. Ciaramella, G. Raiconi, R. Tagliaferri et al., Data Visualization Methodologies for Data Mining Systems in Bioinformatics, IJCNN 2005, special session on Neural Networks Applications in Bioinformatics, Montreal (Canada), 2005 

35. A. Staiano, L. De Vinco, R. Tagliaferri, G. Longo et al., Probabilistic Principal Surfaces for Yeast Gene Microarray Data Mining, Fourth IEEE International Conference on Data Mining: ICDM 2004. IEEE ISBN 0-7695-2142-8, pp. 202-209, Brighton, UK, 2004 

36. A. Staiano, L. De Vinco, R. Tagliaferri, G. Longo et al., Mining Yeast Gene Microarray Data with Latent Variable Models, WIRN04, Perugia (Italy), 2004, Biological and Artificial Environments, 2005, ISBN: 1-4020-3431, Apolloni, Marinaro, Tagliaferri (Eds), Kluwer, 2005

37. A. Staiano, R. Tagliaferri, G. Longo, Committee of Spherical Probabilistic Principal Surfaces, International Joint Conference on Neural Networks, Budapest, 2004

38. A. Staiano, L. De Vinco, R. Tagliaferri, G. Longo, High-D Data Visualization Methods via Probabilistic Principal Surfaces for Data Mining Applications, Multimedia Database and Image Communication, Salerno (Italy), June 2004, Series on Software Engineering and Knowledge Engineering - World Scientific - Series, vol. 17, pp. 63-74, 2005

39. A. Staiano, R. Tagliaferri, W. Pedrycz, Linear regression model-guided clustering for training RBF Neural Networks for regression problems, LNCS Vol. 2955/2006, pp. 127-132. Fuzzy Logic and Applications: 5th International Workshop, WILF 2003 

40. S. Sessa, G. Longo, R. Tagliaferri, A. Ciaramella, A. Staiano, Fuzzy Similarities in Stars/Galaxies Classification, (invited paper), IEEE Conference on System Man and Cybernetics, Tunisia, 2002

41. R. Tagliaferri, G. Longo, A. Staiano et al., Data mining of large astronomical databases with neural tools, SPIE 2002 Waikoloa Hawai, vol. 4847-49, pp. 265-276, 2002 

42. A. Staiano et al., Artificial Intelligence Tools for Visualization and data Mining in Large Astronomical Databases, ESO/ESA/NASA/NSF Astronomy Conference, Garching, Germania, June 10 - 14, 2002, Springer-Verlag, Vol. 15/2004, pp. 202-213, 2004 

43. G. Longo, R. Tagliaferri, A. Staiano et al., Advanced Data Mining Tools for Exploring Large Astronomical Databases, SPIE’s 46th An- nual Meeting International Symposium on Optical Science and Technology, San Diego, CA, USA, 2001

44. R. Tagliaferri, A. Staiano, D. Scala, A Supervised Fuzzy Clustering Algorithm for training Radial Basis Function Neural Networks, IFSA/NAFIPS 2001, Vancouver, Canada, 2001 

45. A. Di Nola, V. Loia, A. Staiano, Genetic-based Spatial Clustering, FUZZ - IEEE 2000, May 7-10, S. Antonio, Texas, U.S.A., 2000

46. V. Loia, S. Sessa, A. Staiano, R. Tagliaferri, An Evolutionary Hybrid Approach to the Design of a Decision-Support System, ACM SAC 2000, Track on Fuzzy Applications, March 2000, Como, Italy, 2000