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Davide Nardone, Andelo Ciaramella, Antonino Staiano, A Sparse-Modeling Based Approach for Class Specific Feature Selection, PeerJ Computer Science, 5:e237, doi.org/10.7717/peerj-cs.237, 2019
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Davide Nardone, Andelo Ciaramella, Antonino Staiano, A Sparse-Modeling Based Approach for Class Specific Feature Selection, PeerJ Computer Science, 5:e237, doi.org/10.7717/peerj-cs.237, 2019
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<p>Antonio Maratea, Angelo Ciaramella, Giuseppe Pio Cianci, Record linkage of banks and municipalities through multiple criteria and neural networks, PeerJ Computer Science 6:e258 <a href="https://doi.org/10.7717/peerj-cs.258,">https://doi.org/10.7717/peerj-cs.258,</a> 2020</p>
<p>Davide Nardone, Andelo Ciaramella, Antonino Staiano, A Sparse-Modeling Based Approach for Class Specific Feature Selection, PeerJ Computer Science, 5:e237, doi.org/10.7717/peerj-cs.237, 2019</p>
<p>Angelo Ciaramella, Antonino Staiano, On the Role of Clustering and Visualization Techniques in Gene Microarray Data, A. Ciaramella, A. Staiano, Algorithms, 12(6), 123, 2019</p>
<p>Alessio Ferone, Antonio Maratea: Integrating rough set principles in the graded possibilistic clustering. <strong>Information Sciences</strong>. 477: 148-160 (2019)</p>
<p>Elena Chianese, Francesco Camastra, Angelo Ciaramella, Tony Christian Landi, Antonino Staiano, Angelo Riccio: Spatio-temporal learning in predicting ambient particulate matter concentration by multi-layer perceptron. <strong>Ecological Informatics</strong> 49: 54-61 (2019)</p>
<p>Silvio Barra, Maria De Marsico, Michele Nappi, Fabio Narducci, Daniel Riccio: A hand-based biometric system in visible light for mobile environments. <strong>Information Sciences</strong>. 479: 472-485 (2019)</p>
<p>Battistone, Francesco, Alfredo Petrosino: TGLSTM: A time based graph deep learning approach to gait recognition. <strong>Pattern Recognition Letters</strong> (in press).</p>
<p>Freire-Obregón, D., Narducci, F., Barra, S., Castrillón-Santana, M.: Deep learning for source camera identification on mobile devices. <strong>Pattern Recognition Letters</strong> (in press)</p>
<p>L. Maddalena and A. Petrosino, Self-Organizing Background Subtraction Using Color and Depth Data, <strong>Multimedia Tools and Applications</strong>, Springer, (in press).</p>
<p>Lucia Maddalena, Alfredo Petrosino, Background Subtraction for Moving Object Detection in RGBD Data: A Survey. J. <strong>Imaging</strong> 4(5): 71 (2018)</p>
<p>Francesco Battistone, Alfredo Petrosino, Vincenzo Santopietro, Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles. <strong>Signal Processing Systems</strong> 90(6): 891-900 (2018)</p>
<p>Francesco Camastra, Francesco Esposito, Antonino Staiano: Linear SVM-based recognition of elementary juggling movements using correlation dimension of Euler Angles of a single arm. <strong>Neural Computing and Applications</strong> 29(11): 1005-1013 (2018)</p>
<p>Alessio Ferone: Feature selection based on composition of rough sets induced by feature granulation. <strong>Internatioanl Journal Approximate Reasoning</strong> 101: 276-292 (2018)</p>
<p>Silvio Barra, Kim-Kwang Raymond Choo, Michele Nappi, Arcangelo Castiglione, Fabio Narducci, Rajiv Ranjan: Biometrics-as-a-Service: Cloud-Based Technology, Systems, and Applications. <strong>IEEE Cloud Computing</strong> 5(4): 33-37 (2018)</p>
<p>Maria De Marsico, Michele Nappi, Fabio Narducci, Hugo Proença: Insights into the results of MICHE I - Mobile Iris CHallenge Evaluation. <strong>Pattern Recognition</strong> 74: 286-304 (2018)</p>
<p>Antonio Maratea, Alfredo Petrosino, Mario Manzo: User Click Modeling on a Learning Management System. <strong>IJHCITP</strong> 8(4): 38-49 (2017)</p>
<p>Alfredo Petrosino, Lucia Maddalena, Thierry Bouwmans: Editorial-Scene background modeling and initialization. <strong>Pattern Recognition Letters</strong> 96: 1-2 (2017)</p>
<p>Thierry Bouwmans, Lucia Maddalena, Alfredo Petrosino: Scene background initialization: A taxonomy. <strong>Pattern Recognition Letters</strong> 96: 3-11 (2017)</p>
<p>Jodoin P-M, Maddalena L., Petrosino A., Wang Y., Extensive Benchmark and Survey of Background Modeling Methods. <strong>IEEE Transactions on Image Processing</strong> 26 (11) : 5244-5256 (2017)</p>
<p>Aniello Castiglione, Kim-Kwang Raymond Choo, Michele Nappi, Fabio Narducci: Biometrics in the Cloud: Challenges and Research Opportunities. <strong>IEEE Cloud Computing</strong> 4(4): 12-17 (2017)</p>
<p>Andrea F. Abate, Silvio Barra, Luigi Gallo, Fabio Narducci: Kurtosis and skewness at pixel level as input for SOM networks to iris recognition on mobile devices. <strong>Pattern Recognition Letters</strong> 91: 37-43 (2017)</p>
<p>H. Fu, Y. Wei, F. Camastra, P. Aricò, H. Sheng, Advances in Eye Tracking Technology: Theory, Algorithms, and Applications. <strong>Comp. Int. and Neurosc.</strong> 2016: 7831469:1-7831469:2 (2016)</p>
<p>F. Camastra, A. Staiano, Intrinsic dimension estimation: Advances and open problems. <strong>Information Sciences</strong>. 328: 26-41 (2016)</p>
<p>M. De Marsico, A. Petrosino, S. Ricciardi, Iris recognition through machine learning techniques: A survey. <strong>Pattern Recognition Letters</strong> 82: 106-115 (2016)</p>
<p>Angelo Ciaramella, Giulio Giunta: Packet loss recovery in audio multimedia streaming by using compressive sensing. <strong>IET Communications</strong> 10(4): 387-392 (2016)</p>
<p>Angelo Ciaramella, Marco Gianfico, Giulio Giunta: Compressive sampling and adaptive dictionary learning for the packet loss recovery in audio multimedia streaming. <strong>Multimedia Tools Appl.</strong> 75(24): 17375-17392 (2016)</p>
<p>João C. Neves, Fabio Narducci, Silvio Barra, Hugo Proença: Biometric recognition in surveillance scenarios: a survey. <strong>Artificial Intelligence Review</strong> 46(4): 515-541 (2016)</p>
<p>Fabio Narducci, Stefano Ricciardi, Raffaele Vertucci: Enabling consistent hand-based interaction in mixed reality by occlusions handling. <strong>Multimedia Tools Appl.</strong> 75(16): 9549-9562 (2016)</p>
<p>S. Iodice, A. Petrosino, Salient feature based graph matching for person re-identification. <strong>Pattern Recognition</strong> 48(4): 1074-1085 (2015)</p>
<p>A. Petrosino, Special Section: ICIAP 2013 Awards. <strong>Pattern Recognition Letters</strong> 55: 34 (2015)</p>
<p>F. Camastra, R. Amato, M. D. Di Taranto, A. Staiano, Advances in Computational Methods for Genetic Diseases. <strong>Comp. Math. Methods in Medicine</strong> 2015: 645649:1-645649:2 (2015)</p>
<p>F. Camastra, M. D. Di Taranto, A. Staiano, Statistical and Computational Methods for Genetic Diseases: An Overview. <strong>Comp. Math. Methods in Medicine</strong> 2015: 954598:1-954598:8 (2015)</p>
<p>F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace, A fuzzy decision system for genetically modified plant environmental risk assessment using Mamdani inference. <strong>Expert Syst. Appl.</strong> 42(3): 1710-1716 (2015)</p>
<p>Francesco Camastra, Angelo Ciaramella, Valeria Giovannelli, Matteo Lener, Valentina Rastelli, Antonino Staiano, Giovanni Staiano, Alfredo Starace: A fuzzy decision system for genetically modified plant environmental risk assessment using Mamdani inference. <strong>Expert Syst. Appl.</strong> 42(3): 1710-1716 (2015)</p>
<p>Silvio Barra, Andrea Casanova, Fabio Narducci, Stefano Ricciardi: Ubiquitous iris recognition by means of mobile devices. <strong>Pattern Recognition Letters</strong> 57: 66-73 (2015)</p>
<p>A. Ferone, L. Maddalena, Neural Background Subtraction for Pan-Tilt-Zoom Cameras. <strong>IEEE Trans. Systems, Man, and Cybernetics: Systems</strong> 44(5): 571-579 (2014)</p>
<p>L. Maddalena, A. Petrosino, The 3dSOBS+ algorithm for moving object detection. <strong>Computer Vision and Image Understanding</strong> 122: 65-73 (2014)</p>
<p>A. Maratea, A. Petrosino, M. Manzo, Adjusted F-measure and kernel scaling for imbalanced data learning. <strong>Informaiton Sciences</strong> 257: 331-341 (2014)</p>
<p>L. Maddalena, A. Petrosino, F. Russo, People counting by learning their appearance in a multi-view camera environment. <strong>Pattern Recognition Letters</strong> 36: 125-134 (2014)</p>
<p>A. Albanese, S. K. Pal, A. Petrosino, Rough Sets, Kernel Set, and Spatiotemporal Outlier Detection. <strong>IEEE Trans. Knowl. Data Eng.</strong> 26(1): 194-207 (2014)</p>
<p>A. Petrosino, S. K. Pal, Guest Editorial on Decision Making in Human and Machine Vision. <strong>IEEE Trans. Systems, Man, and Cybernetics: Systems</strong> 44(5): 521-522 (2014)</p>
<p><!-- raw HTML omitted -->Francesco Camastra, Angelo Ciaramella, Valeria Giovannelli, Matteo Lener, Valentina Rastelli, Antonino Staiano, Giovanni Staiano, Alfredo Starace: TÉRA: A tool for the environmental risk assessment of genetically modified plants. <strong>Ecological Informatics</strong> 24: 186-193 (2014)<!-- raw HTML omitted --></p>
<p>V. Cantoni, A. Ferone, O. Ozbudak, A. Petrosino, Protein motifs retrieval by SS terns occurrences, <strong>Pattern Recognition Letters</strong> 34(5): 559-563 (2013) - <a href="/pdf/Protein.pdf">PDF</a> - <a href="/bib/Protein.bib">BibTeX</a></p>
<p>R. Melfi, S. Kondra, A. Petrosino, Human activity modeling by spatio temporal textural appearance. <strong>Pattern Recognition Letters</strong> 34(15): 1990-1994 (2013)</p>
<p>L. Maddalena, A. Petrosino, Stopped Object Detection by Learning Foreground Model in Videos. <strong>IEEE Trans. Neural Netw. Learning Syst.</strong> 24(5): 723-735 (2013)</p>
<p>F. Camastra, A. Ciaramella, A. Staiano, Machine learning and soft computing for ICT security: an overview of current trends. <strong>J. Ambient Intelligence and Humanized Computing</strong> 4(2): 235-247 (2013)</p>
<p>L. Lamberti, F. Camastra, Handy: A real-time three color glove-based gesture recognizer with learning vector quantization, <strong>Expert Syst. Appl.</strong> 39(12): 10489-10494 (2012) - <a href="/pdf/esa11_rev.pdf">PDF</a> - <a href="/bib/esa11_rev.bib">BibTex</a></p>
<p>A. Ferone, L. Maddalena, Neural Background Subtraction for PTZ Cameras, <strong>IEEE Transactions on Systems, Man, and Cybernetics: Systems</strong>, accepted - [PDF](/pdf/Neural Background Subtraction for PTZ Cameras.pdf) - BibTeX</p>
<p>A. Albanese, S. K. Pal, A. Petrosino, Rough Sets, Kernel Set and Spatio-Temporal Outlier Detection, <strong>IEEE Transactions on Knowledge and Data Engineering(99)</strong>: 1 (2012) - [PDF](/pdf/Rough Sets, Kernel Set and Spatio-Temporal Outlier Detection.pdf) - [BibTeX](/bib/Rough Sets, Kernel Set and Spatio-Temporal Outlier Detection.bib)</p>
<p>A. Petrosino, M. Miralto, A. Ferone, A real-time streaming server in the RTLinux environment using VideoLanClient, <strong>J. Real-Time Image Processing 6</strong>(4): 247-256 (2011) - [PDF](/pdf/A real-time streaming server in the RTLinux environment using VideoLanClient.pdf) - [BibTeX](/bib/A real-time streaming server in the RTLinux environment using VideoLanClient.bib)</p>
<p>A. Ciaramella, E. De Lauro, S. De Martino, M. Falanga, R. Tagliaferri: Modeling and Generating Organ Pipes Self-Sustained Tones by Using ICA. J. Signal and Information Processing 2(3): 141-151 (2011) - <a href="JSIP20110300017_53298522.pdf">PDF</a> - <a href="/bib/JSIP20110300017_53298522.bib">BibTeX</a></p>
<p>L. Maddalena, A. Petrosino, A fuzzy spatial coherence-based approach to background/foreground separation for moving object detection, Neural Computing and Applications 19(2): 179-186 (2010) - [PDF](/pdf/A Fuzzy Spatial Coherence based Approach to Background Foreground Separation for Moving Object Detection.pdf) - [BibTeX](/bib/A Fuzzy Spatial Coherence based Approach to Background Foreground Separation for Moving Object Detection.bib)</p>
<p>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 of interferon therapy in multiple sclerosis patients, Information Sciences, Vol. 180, Issue 21, pp. 4153-4163, (2010) - <a href="/pdf/2010_therapy.pdf">PDF</a> - <a href="/bib/2010_therapy.bib">BibTeX</a></p>
<p>L. Maddalena, A. Petrosino, “A Fuzzy Spatial Coherence-based Approach to Background/ Foreground Separation for Moving Object Detection”, Neural Computing and Applications19(2):179-186, (2010) - PDF - BibTeX</p>
<p>Interactive data analysis and clustering of genomic data, A. Ciaramella, S. Cocozza, F. Iorio,G. Miele, F. Napolitano, M. Pinelli, G. Raiconi, R. Tagliaferri, Neural Networks, vol. 21,Issues 2-3, pp. 368-378, ISSN: 0893-6080, doi: 10.1016/ j.neunet.2007.12.026, 2008;</p>
<p>Clustering and visualization approaches for human cell cycle gene expression data analysis, F. Napolitano, G. Raiconi, R. Tagliaferri, A. Ciaramella, A. Staiano, G. Miele,InternationalJournal of Approximate Reasoning, vol. 47, Issue 1, pp. 70-84, ISSN: 0888-613,doi:10.1016/j.ijar.2007.03.013, 2008;</p>
<p>Neural Network Techniques for Proactive Password Checking, A. Ciaramella, P. D’Arco, A.De Santis, C. Galdi, R. Tagliaferri,IEEE Transactions on Dependable and SecureComputing, Volume 3, Issue 4, Oct.-Dec. 2006 Page(s):327 - 339, ISSN: 1545-5971,doi:10.1109/TDSC.2006.53, 2006;</p>
<p>A Multi-Step Approach to Time Series Analysis and Gene Expression Clustering, R. Am-ato, A. Ciaramella, N. Deniskina, C. Del Mondo, D. di Bernardo, C. Donalek, G. Longo, G.Mangano, G. Miele, G. Raiconi, A. Staiano, R. Tagliaferri,Bioinformatics, vol. 22, n. 5, pp.589-596, ISSN: 1367-4803, doi: 10.1093/bioinformatics/btk026, 2006;</p>
<p>Fuzzy Relational Neural Network, A. Ciaramella, R. Tagliaferri, W. Pedrycz, A. Di Nola,International Journal of Approximate Reasoning, vol. 41, pp. 146-163, ISSN: 0888-613, doi:10.1016/j.ijar.2005.06.016, 2006;</p>
<p>ICA Based Identification of Dynamical Systems Generating Synthetic and Real World TimeSeries, A. Ciaramella, E. De Lauro, S. De Martino, M. Falanga, R. Tagliaferri,Soft Com-puting, vol. 10, pp. 587-606, ISSN: 1432-7643, doi: 10.1007/s00500-005-0515-7, 2006;</p>
<p>Separation of Convolved Mixtures in Frequency Domain ICA, A. Ciaramella, M. Funaro,R. Tagliaferri,International Mathematical Forum, vol. 1, no. 16, pp. 769-795, ISSN:1312-7594, doi: 10.12988/imf, 2006;</p>
<p>Complexity of Time Series Associated to Dynamical Systems Inferred from IndependentComponent Analysis, A. Ciaramella, E. de Lauro, S. De Martino, M. Falanga, R. Tagli-aferri,Physical Review E., 72, 046712-1/14, ISSN: 1539-3755, doi:10.1103/Phys-RevE.72.046712, 2005;</p>
<p>Novel Techniques for Microarry Data Analysis, A. Ciaramella, R. Amato, A. Staiano, R.Tagliaferri, et al.,Journal of Theoretical and Computational Nanoscience, vol. 2, n.4, pp. 514-523, ISSN: 1546-1955, doi: <a href="http://dx.doi.org/">http://dx.doi.org/</a> 10.1166/ jctn.2005.006, 2005;</p>
<p>Applications of Neural Networks in Astronomy and Astroparticle Physics, A. Ciaramella,E. Donalek, A. Staiano, et al.,Recent Res. Devel. Astrophys., vol. 2, pp. 27-58,ISBN:9788177362954, 2005;</p>
<p>The Genetic Development of Ordinal Sums, A. Ciaramella, W. Pedrycz, R. Tagliaferri,FuzzySets and Systems, vol. 151, pp. 303-325, doi: 10.1016/j.fss.2004.07.003, ISSN: 0165-0114, 2005;</p>
<p>Characterization of Strombolian Events by Using Independent Component Analysis, A. Cia-ramella, E. De Lauro, S. De Martino, B. Di Lieto, M. Falanga, R. Tagliaferri,NonlinearProcesses in Geophysics, vol. 11, pp. 453-461, ISSN: 1023-5809, 2004;</p>
<p>A Multifrequency Analysis of Radio Variability of Blazars, A. Ciaramella, C. Bongardo, H.D. Aller, M. F. Aller, G. De Zotti, A. Lähteenmaki, G. Longo, L. Milano, R. Tagliaferri, H.Teräsranta, M. Tornikoski, S. Urpo,Astronomy & Astrophysics Journal, vol. 419, pp.485-500, ISSN: 0004-6361, doi:10.1051/0004-6361:20035771, 2004;</p>
<p>Polarisation analysis of the independent components of low frequency events at Strombolivolcano (Eolian Islands, Italy), F. Acernese , A. Ciaramella, S. De Martino, M. Falanga, C.Godano, R. Tagliaferri,Journal of Volcanology and Geothermal Research, ElsevierJournals, n. 137, pp. 153-168, ISSN: 0377-0273, doi:10.1016/j.jvolgeores.2004.05.005,2004;</p>
<p>Neural Networks in Astronomy, R. Tagliaferri, G. Longo, L. Milano, F. Acernese, F. Barone,A. Ciaramella, R. De Rosa, C. Donalek, A. Eleuteri, G. Raiconi, S. Sessa, A. Staiano, A.Volpicelli,Neural Networks, vol. 16, N. 3-4, pp. 295-319, 2003, ISSN: 0893-6080,doi:10.1016/S0893-6080(03)00028-5, 2003;</p>
<p>Neural Networks for Blind-Source Separation of Stromboli Explosion Quakes, F. Acernese,A. Ciaramella, S. De Martino, R. De Rosa, M. Falanga, R. Tagliaferri,IEEE Transac-tions on Neural Networks, vol. 14, Issue: 1, pp. 167-175, ISSN: 1045-9227,doi:10.1109/TNN.2002.806649, 2003;</p>
<p>Soft Computing Methodologies for Spectral Analysis in Cyclostratigraphy, R. Tagliaferri, N.Pelosi, A. Ciaramella, G. Longo, M. Milano, F. Barone,Computers and Geosciences, vol.27, issue 5, pp. 535-548, ISSN: 0098-3004, doi: 10.1016/S0098-3004(00)00166-7, 2001;</p>
<p>Spectral Analysis of Stellar Light Curves by Means of Neural Networks, R. Tagliaferri, A.Ciaramella, L.Milano, F. Barone, G. Longo,Astronomy and Astrophysics SupplementSeries, vol. 137, pp. 391-405, ISSN: 0004-6361, 1999;</p>
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