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      <title>Books</title>
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      <description>&lt;p&gt;&lt;a href=&#34;https://www.springer.com/gp/book/9781447167341&#34;&gt;Machine Learning for Audio, Image and Video Analysis&lt;/a&gt;&lt;br&gt;
Camastra Francesco, Vinciarelli Alessandro&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;https://www.crcpress.com/Handbook-on-Soft-Computing-for-Video-Surveillance/Pal-Petrosino-Maddalena/p/book/9781439856840&#34;&gt;Handbook on Soft Computing for Video Surveillance&lt;/a&gt;&lt;br&gt;
S.K. Pal, A. Petrosino, L. Maddalena (Eds), Chapman &amp;amp; Hall/CRC&lt;br&gt;
ISBN: 9781439856840, 2012.\&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;https://www.springer.com/gp/book/9783642237126&#34;&gt;Fuzzy Logic and Applications, Lecture Notes in Computer Science, vol. 6857&lt;/a&gt;&lt;br&gt;
Anna Maria Fanelli, Witold Pedrycz, Alfredo Petrosino (Eds.), Springer 2011, isbn 978-3-642-23712-6\&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;https://www.springer.com/it/book/9783540325291&#34;&gt;Fuzzy Logic and Applications, Lecture Notes in Computer Science, vol. 3849&lt;/a&gt;&lt;br&gt;
Bloch, Isabelle; Petrosino, Alfredo; Tettamanzi, Andrea G.B. (Eds.), Springer-Verlag, 2006, ISBN: 3-540-32529-8\&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;https://www.springer.com/it/book/9783540310198&#34;&gt;Fuzzy Logic and Applications, Lecture Notes in Computer Science, vol. 2955&lt;/a&gt;&lt;br&gt;
Di Gesù, Vito; Masulli, Francesco; Petrosino, Alfredo (Eds.), 2005&lt;br&gt;
ISBN: 3-540-31019-3.\&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;http://kluwer.m0.net/m/s.asp?HB6920827412X1557354X127314Xjo%40plenum.co.uk&#34;&gt;Visual Attention Mechanisms&lt;/a&gt;&lt;br&gt;
Cantoni V., Marinaro M., Petrosino A., Ed.s, Kluwer, 2002.\&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;http://cvprlab.uniparthenope.it/publications/new_trends_in_fuzzy_logic_ii_files/papers.htm&#34;&gt;New Trends in Fuzzy Logic II&lt;/a&gt;&lt;br&gt;
Castellano M., Blonda P., Petrosino A. Ed.s, World Scientific Publishing, Singapore,1998.\&lt;/p&gt;
&lt;p&gt;&lt;a href=&#34;http://cvprlab.uniparthenope.it/publications/new_trends_in_fuzzy_logic_files/papers.htm&#34;&gt;New Trends in Fuzzy Logic&lt;/a&gt;&lt;br&gt;
Bonarini A., Mancini A., Masulli F., Petrosino A. Ed.s, World Scientific Publishing, Singapore, 1996\&lt;/p&gt;
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      <title>Conference Papers</title>
      <link>/publications/conference/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>/publications/conference/</guid>
      <description>&lt;p&gt;Compressive Sensing and Hierarchical Clustering for Microarray Data with Missing Values, A. Ciaramella, D. Nardone, A. Staiano, Lecture Notes in Bioinformatics, “Computational Intelligence Methods for Bioinformatics and Biostatistics”, ISBN 978-3-030-34585-3;&lt;/p&gt;
&lt;p&gt;Semantic Maps for Knowledge Management of Web and Social Information, Camastra, F., Ciaramella, A., Maratea, A., Son, L.H., Staiano, A. (2020) Studies in Computational Intelligence, 837, pp. 39-51&lt;/p&gt;
&lt;p&gt;Blind Source Separation Using Dictionary Learning in Wireless Sensor Network Scenario, A. Ciaramella, D. Nardone, A. Staiano (2020) . In: Esposito A., Faundez-Zanuy M., Morabito F., Pasero E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151. Springer, Singapore;&lt;/p&gt;
&lt;p&gt;Fuzzy Similarity-based Hierarchical Clustering for Atmospheric Pollutants Prediction, F. Camastra, A. Ciaramella, A. Riccio, S. Le Hoang, A. Staiano, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11291 LNAI, pp. 123-133, 2019;&lt;/p&gt;
&lt;p&gt;Content-based music agglomeration by sparse modeling and convolved independent component analysis, M. Iannicelli, D. Nardone, A. Ciaramella, A. Staiano, (2019) Smart Innovation, Systems and Technologies, 103, pp. 87-96;&lt;/p&gt;
&lt;p&gt;Fuzzy  clustering  of  structured  data:  Some  preliminary  results,  G.  Vettigli,  A.  Ciaramella, IEEE International Conference on Fuzzy Systems, art. no. 8015648, 2017;&lt;/p&gt;
&lt;p&gt;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, F. Camastra, A. Ciaramella, A. Staiano, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10613 LNCS, pp.407-414, 2017;&lt;/p&gt;
&lt;p&gt;Semantic  maps  of  Twitter  conversations,  A.  Ciaramella,  A.  Maratea,  E.  Spagnoli,  Smart Innovation, Systems and Technologies, 69, pp. 327-338, 2017;&lt;/p&gt;
&lt;p&gt;A bayesian-based neural network model for solar photovoltaic power forecasting,  A. Ciaramella, A. Staiano, G. Cervone, S. Alessandrini, Smart Innovation, Systems and Technologies, 54, pp. 169-177, ISSN: 21903018, doi: 10.1007/978-3-319-33747-0_17, 2016;&lt;/p&gt;
&lt;p&gt;A Fuzzy Decision Support System for the Environmental Risk Assessment of genetically modified organisms,  F. Camastra,  A. Ciaramella,  V. Giovannelli,  M. Lener,  V. Rastelli,  A. Staiano, G. Staiano, A. Starace,Smart Innovation, Systems and Technologies, 26,pp. 241-249, ISSN: 21903018, doi: 10.1007/978-3-319-04129-2_24, 2014;&lt;/p&gt;
&lt;p&gt;Environmental Risk  Assessment of  Genetically Modified Organisms  by a  Fuzzy Decision Support System, F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace, LNCS, vol. 8158, p. 428-435, ISBN: 978-3-642-41189-2, ISSN:0302-9743, doi: 10.1007/978-3-642-41190-846, 2013;&lt;/p&gt;
&lt;p&gt;Rule Learning in a Fuzzy Decision Support System for the Environmental Risk Assessment of GMOs, F. Camastra, A. Ciaramella, V. Giovannelli, M. Lener, V. Rastelli, A. Staiano, G. Staiano, A. Starace, LNAI, vol. 8256, p. 226-233, ISBN: 978-3-319-03199-6, ISSN:0302-9743, doi: 10.1007/978-3-319-03200-923, 2013;&lt;/p&gt;
&lt;p&gt;Comparison of Dispersion Models by Using Fuzzy Similarity Relations,   A. Ciaramella,  A. Riccio, S. Galmarini, G. Giunta, S. Potempski, LNCS, vol. 6934; p. 57-67, ISSN: 0302-9743, doi:10.1007/978-3-642-23954-0_8, 2011;&lt;/p&gt;
&lt;p&gt;Uninorm Based Fuzzy Network for Tree Data Structures,  A. Ciaramella,  W. Pedrycz,  A. Petrosino, LNAI 5571, pp. 77-84, ISSN: 0302-9743, doi: 10.1007/978-3-642-02282-1_10, 2009;&lt;/p&gt;
&lt;p&gt;Statistical and Fuzzy Approaches for Atmospheric Boundary Layer Classification, A. Ciaramella, A. Riccio, F. Angelini, G. P. Gobbi, T. C. Landi, LNAI 5853, pp. 375-384, ISSN: 0302-9743, doi:10.1007/978-3-642-10291-2_38, 2009;&lt;/p&gt;
&lt;p&gt;Independent Data Model Selection for Ensemble Dispersion Forecasting, A. Ciaramella, G. Giunta, A. Riccio, S. Galmarini, Book: Applications of Supervised and Unsupervised Ensemble Methods Series: Studies in Computational Intelligence, Vol.  245, pp. 213-231, ISSN: 1860-949X, doi: 10.1007/978-3-642-03999-7_12, 2009;&lt;/p&gt;
&lt;p&gt;Single Channel Polyphonic Music Transcription,  A. Ciaramella,Frontiers in Artificial Intelligence and Applications (IOS),  vol.   193, pp. 99-108, ISSN: 0922-6389, doi:10.3233/978-1-58603-984-4-99, 2009&lt;/p&gt;
&lt;p&gt;The Genetic Development of Uninorm-Based Neurons, A. Ciaramella, W. Pedrycz and R. Tagliaferri, LNAI 4578, pp. 69-76, ISSN: 0302-9743, 2007;&lt;/p&gt;
&lt;p&gt;Clustering,  Assessment and Validation:  an application to gene expression data,  A. Ciaramella, S. Cocozza, F. Iorio, G. Miele, F. Napolitano, M. Pinelli, G. Raiconi, R. Tagliaferri, Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, USA,August 12-17, 2007, pp. 1419-1425, ISSN: 10987576, doi: 10.1109/IJCNN.2007.4371199, 2007;&lt;/p&gt;
&lt;p&gt;NEC for Gene Expression Analysis, R. Amato, A. Ciaramella, N. Deniskina, et al., LNAI 3849 , pp. 246-251, ISSN: 03029743, doi:10.1007/11676935_30, 2006;&lt;/p&gt;
&lt;p&gt;OR/AND Neurons for Fuzzy Set Connectives Using Ordinal Sums and Genetic Algorithms, A. Ciaramella, W. Pedrycz, R. Tagliaferri, LNAI 3849, pp.  188-194, ISSN:0302-9743, doi: 10.1007/11676935_23, 2006;&lt;/p&gt;
&lt;p&gt;NEC: a Hierarchical Agglomerative Clustering Based on Fisher and Negentropy Information, A. Ciaramella, G. Longo, A. Staiano, R. Tagliaferri, LNCS 3931, pp. 49-56, ISSN: 03029743, doi: 10.1007/11731177_8, 2006;&lt;/p&gt;
&lt;p&gt;Fuzzy Relational Neural Network for Data Analysis, A. Ciaramella, W. Pedrycz, R. Tagliaferri, A. Di Nola, LNAI 2955, pp. 103 - 109, ISSN: 0302-9743, 2006;&lt;/p&gt;
&lt;p&gt;BSS Toolbox for Delayed and Convolved Mixtures, A. Ciaramella, F. Iorio, R. Tagliaferri, Proceedings of IEEE International Joint Conference on Neural Networks 2005 (IJCNN05), vol. 2, pp. 1245 - 1250,ISBN: 0780390482;978-078039048-5, doi: 10.1109 /IJCNN.2005.1556032,2005;&lt;/p&gt;
&lt;p&gt;Data Visualization Methodologies for Data Mining Systems in Bioinformatics, A. Ciaramella, A. Staiano, R. Tagliaferri et al., Proceedings of IEEE International Joint Conference on Neural Networks 2005 (IJCNN05), vol. 1, pp. 143 - 148, ISBN: 0780390482;978-078039048-5, doi:10.1109 /IJCNN.2005.1555820, 2005;&lt;/p&gt;
&lt;p&gt;Visualization, Clustering and Classification of Multidimensional Astronomical Data, A. Ciaramella,  A. Staiano,  R. Tagliaferri et al.,   Proceedings of IEEE International Workshop onComputer Architecture for Machine Perception (CAMP05 ), pp. 141 - 146, 2005;&lt;/p&gt;
&lt;p&gt;Inference  Systems  by  Using  Ordinal  Sums  and  Genetic  Algorithms,  A.  Ciaramella,  W. Pedrycz, R. Tagliaferri, Proceedings of NAFIPS 2004, IEEE Annual Meeting of the Fuzzy Information, vol.2, pp. 629 - 634, 2004;&lt;/p&gt;
&lt;p&gt;Fuzzy Neural Networks Based on Fuzzy Logic Algebras Valued Relations, R. Tagliaferri, A. Ciaramella, A. Di Nola, R. Belohlavek,“Fuzzy Partial Differential Equations and Relational Equations: Reservoir Characterization and Modeling”, M. Nikravesh,L.A. Zadeh, V. Korotnihk (Eds.), Springer-Verlag, ISBN: 978-3-540-20322-3, doi: 10.1007/978-3-540-39675-8_3, 2004;&lt;/p&gt;
&lt;p&gt;Ordinal Sums by Using Genetic Algorithms , A. Ciaramella, W. Pedrycz, R. Tagliaferri, Proceedings of FUZZ-IEEE 2004, IEEE International Conference on Fuzzy Systems, vol. 2, pp. 641-646, ISSN: 10987584, doi: 10.1109 /FUZZY.2004.1375472, 2004;&lt;/p&gt;
&lt;p&gt;ICA  for  Modelling  and  Generating  Organ  Pipes  Self-sustained  Tones,  A.  Ciaramella,  E. De Lauro, S. De Martino, M. R. Falanga, R. Tagliaferri, Proceedings of IJCNN 2004, IEEE International Joint Conference on Neural Networks, pp. 261-266, ISSN: 10987576, 2004;&lt;/p&gt;
&lt;p&gt;Probabilistic principal surfaces for yeast gene microarray data mining,  A. Staiano,  L. De Vinco, A. Ciaramella, G. Raiconi, R. Tagliaferri, R. Amato, G. Longo, C. Donalek, G. Miele, D.D. Bernardo, Proceedings of IEEE Conference on Data Mining, Brighton, UK, 1-4 Novembre, ISBN: 0769521428;978-076952142-8, doi: 10.1109/ICDM.2004.10088, 2004;&lt;/p&gt;
&lt;p&gt;Amplitude and Permutation Indeterminacies in Frequency Domain Convolved ICA, A. Ciaramella,  R. Tagliaferri,  Proceedings of the IEEE International Joint Conference on Neural Networks 2003, vol. 1, pp. 708-713, 2003;&lt;/p&gt;
&lt;p&gt;Fuzzy Similarities in Stars/Galaxies Classification , S. Sessa , R. Tagliaferri, G. Longo, A. Ciaramella, A. Staiano, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, vol. 2 , pp. 494-496, ISSN: 08843627, 2002;&lt;/p&gt;
&lt;p&gt;Fuzzy relations neural network:  Some preliminary results, A. Ciaramella, W. Pedrycz, R. Tagliaferri, Proceedings of the 10th IEEE International Conference on Fuzzy Systems, vol. 1, pp. 469-472, 2001;&lt;/p&gt;
&lt;p&gt;Two-layer Fuzzy Relational Networks: some preliminary results, A. Ciaramella, W. Pedrycz, R.  Tagliaferri,  Proceedings  of  the  Atlantic  Symposium  on  Computational  Biology  and Genome Information Systems &amp;amp; Thecnology (CBGI) 2001, pp.  82-86, ISBN: 0970789009, 2001;&lt;/p&gt;
&lt;p&gt;Advanced Data Mining Tools for Exploring Large Astronomical Data Bases, G. Longo, R. Tagliaferri, S. Sessa, P. Ortiz, M. Capaccioli, A. Ciaramella, C. Donalek, G. Raiconi, A. Staiano, A. Volpicelli, SPIE’s 46th Annual Meeting International Symposium on Optical Scienceand Technology, pp. 61-75, ISSN: 0277786X, doi: 10.1117/12.447191, 2001;&lt;/p&gt;
&lt;p&gt;Hybrid Neural Networks for Frequency Estimation of Unevenly Sampled Data, F. Barone, A.  Ciaramella,  L.  Milano,  R.  Tagliaferri,  G.  Longo,  Proceedings  of  the  International  JointConference on Neural Networks (IJCNN), vol. II, pp. 975-979, 2000;&lt;/p&gt;
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      <title>Journal Papers</title>
      <link>/publications/journal/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>/publications/journal/</guid>
      <description>&lt;p&gt;Antonio Maratea, Angelo Ciaramella, Giuseppe Pio Cianci, Record linkage of banks and municipalities through multiple criteria and neural networks,  PeerJ Computer Science 6:e258 &lt;a href=&#34;https://doi.org/10.7717/peerj-cs.258,&#34;&gt;https://doi.org/10.7717/peerj-cs.258,&lt;/a&gt; 2020&lt;/p&gt;
&lt;p&gt;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&lt;/p&gt;
&lt;p&gt;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&lt;/p&gt;
&lt;p&gt;Alessio Ferone, Antonio Maratea: Integrating rough set principles in the graded possibilistic clustering. &lt;strong&gt;Information Sciences&lt;/strong&gt;. 477: 148-160 (2019)&lt;/p&gt;
&lt;p&gt;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. &lt;strong&gt;Ecological Informatics&lt;/strong&gt; 49: 54-61 (2019)&lt;/p&gt;
&lt;p&gt;Silvio Barra, Maria De Marsico, Michele Nappi, Fabio Narducci, Daniel Riccio: A hand-based biometric system in visible light for mobile environments. &lt;strong&gt;Information Sciences&lt;/strong&gt;. 479: 472-485 (2019)&lt;/p&gt;
&lt;p&gt;Battistone, Francesco, Alfredo Petrosino: TGLSTM: A time based graph deep learning approach to gait recognition. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; (in press).&lt;/p&gt;
&lt;p&gt;Freire-Obregón, D., Narducci, F., Barra, S., Castrillón-Santana, M.: Deep learning for source camera identification on mobile devices. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; (in press)&lt;/p&gt;
&lt;p&gt;L. Maddalena and A. Petrosino, Self-Organizing Background Subtraction Using Color and Depth Data, &lt;strong&gt;Multimedia Tools and Applications&lt;/strong&gt;, Springer, (in press).&lt;/p&gt;
&lt;p&gt;Lucia Maddalena, Alfredo Petrosino, Background Subtraction for Moving Object Detection in RGBD Data: A Survey. J. &lt;strong&gt;Imaging&lt;/strong&gt; 4(5): 71 (2018)&lt;/p&gt;
&lt;p&gt;Francesco Battistone, Alfredo Petrosino, Vincenzo Santopietro, Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles. &lt;strong&gt;Signal Processing Systems&lt;/strong&gt; 90(6): 891-900 (2018)&lt;/p&gt;
&lt;p&gt;Francesco Camastra, Francesco Esposito, Antonino Staiano: Linear SVM-based recognition of elementary juggling movements using correlation dimension of Euler Angles of a single arm. &lt;strong&gt;Neural Computing and Applications&lt;/strong&gt; 29(11): 1005-1013 (2018)&lt;/p&gt;
&lt;p&gt;Alessio Ferone: Feature selection based on composition of rough sets induced by feature granulation. &lt;strong&gt;Internatioanl Journal Approximate Reasoning&lt;/strong&gt; 101: 276-292 (2018)&lt;/p&gt;
&lt;p&gt;Silvio Barra, Kim-Kwang Raymond Choo, Michele Nappi, Arcangelo Castiglione, Fabio Narducci, Rajiv Ranjan: Biometrics-as-a-Service: Cloud-Based Technology, Systems, and Applications. &lt;strong&gt;IEEE Cloud Computing&lt;/strong&gt; 5(4): 33-37 (2018)&lt;/p&gt;
&lt;p&gt;Maria De Marsico, Michele Nappi, Fabio Narducci, Hugo Proença: Insights into the results of MICHE I - Mobile Iris CHallenge Evaluation. &lt;strong&gt;Pattern Recognition&lt;/strong&gt; 74: 286-304 (2018)&lt;/p&gt;
&lt;p&gt;Antonio Maratea, Alfredo Petrosino, Mario Manzo: User Click Modeling on a Learning Management System. &lt;strong&gt;IJHCITP&lt;/strong&gt; 8(4): 38-49 (2017)&lt;/p&gt;
&lt;p&gt;Alfredo Petrosino, Lucia Maddalena, Thierry Bouwmans: Editorial-Scene background modeling and initialization. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 96: 1-2 (2017)&lt;/p&gt;
&lt;p&gt;Thierry Bouwmans, Lucia Maddalena, Alfredo Petrosino: Scene background initialization: A taxonomy. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 96: 3-11 (2017)&lt;/p&gt;
&lt;p&gt;Jodoin P-M, Maddalena L., Petrosino A., Wang Y., Extensive Benchmark and Survey of Background Modeling Methods. &lt;strong&gt;IEEE Transactions on Image Processing&lt;/strong&gt; 26 (11) : 5244-5256 (2017)&lt;/p&gt;
&lt;p&gt;Aniello Castiglione, Kim-Kwang Raymond Choo, Michele Nappi, Fabio Narducci: Biometrics in the Cloud: Challenges and Research Opportunities. &lt;strong&gt;IEEE Cloud Computing&lt;/strong&gt; 4(4): 12-17 (2017)&lt;/p&gt;
&lt;p&gt;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. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 91: 37-43 (2017)&lt;/p&gt;
&lt;p&gt;H. Fu, Y. Wei, F. Camastra, P. Aricò, H. Sheng, Advances in Eye Tracking Technology: Theory, Algorithms, and Applications. &lt;strong&gt;Comp. Int. and Neurosc.&lt;/strong&gt; 2016: 7831469:1-7831469:2 (2016)&lt;/p&gt;
&lt;p&gt;F. Camastra, A. Staiano, Intrinsic dimension estimation: Advances and open problems. &lt;strong&gt;Information Sciences&lt;/strong&gt;. 328: 26-41 (2016)&lt;/p&gt;
&lt;p&gt;M. De Marsico, A. Petrosino, S. Ricciardi, Iris recognition through machine learning techniques: A survey. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 82: 106-115 (2016)&lt;/p&gt;
&lt;p&gt;Angelo Ciaramella, Giulio Giunta: Packet loss recovery in audio multimedia streaming by using compressive sensing. &lt;strong&gt;IET Communications&lt;/strong&gt; 10(4): 387-392 (2016)&lt;/p&gt;
&lt;p&gt;Angelo Ciaramella, Marco Gianfico, Giulio Giunta: Compressive sampling and adaptive dictionary learning for the packet loss recovery in audio multimedia streaming. &lt;strong&gt;Multimedia Tools Appl.&lt;/strong&gt; 75(24): 17375-17392 (2016)&lt;/p&gt;
&lt;p&gt;João C. Neves, Fabio Narducci, Silvio Barra, Hugo Proença: Biometric recognition in surveillance scenarios: a survey. &lt;strong&gt;Artificial Intelligence Review&lt;/strong&gt; 46(4): 515-541 (2016)&lt;/p&gt;
&lt;p&gt;Fabio Narducci, Stefano Ricciardi, Raffaele Vertucci: Enabling consistent hand-based interaction in mixed reality by occlusions handling. &lt;strong&gt;Multimedia Tools Appl.&lt;/strong&gt; 75(16): 9549-9562 (2016)&lt;/p&gt;
&lt;p&gt;S. Iodice, A. Petrosino, Salient feature based graph matching for person re-identification. &lt;strong&gt;Pattern Recognition&lt;/strong&gt; 48(4): 1074-1085 (2015)&lt;/p&gt;
&lt;p&gt;A. Petrosino, Special Section: ICIAP 2013 Awards. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 55: 34 (2015)&lt;/p&gt;
&lt;p&gt;F. Camastra, R. Amato, M. D. Di Taranto, A. Staiano, Advances in Computational Methods for Genetic Diseases. &lt;strong&gt;Comp. Math. Methods in Medicine&lt;/strong&gt; 2015: 645649:1-645649:2 (2015)&lt;/p&gt;
&lt;p&gt;F. Camastra, M. D. Di Taranto, A. Staiano, Statistical and Computational Methods for Genetic Diseases: An Overview. &lt;strong&gt;Comp. Math. Methods in Medicine&lt;/strong&gt; 2015: 954598:1-954598:8 (2015)&lt;/p&gt;
&lt;p&gt;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. &lt;strong&gt;Expert Syst. Appl.&lt;/strong&gt; 42(3): 1710-1716 (2015)&lt;/p&gt;
&lt;p&gt;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. &lt;strong&gt;Expert Syst. Appl.&lt;/strong&gt; 42(3): 1710-1716 (2015)&lt;/p&gt;
&lt;p&gt;Silvio Barra, Andrea Casanova, Fabio Narducci, Stefano Ricciardi: Ubiquitous iris recognition by means of mobile devices. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 57: 66-73 (2015)&lt;/p&gt;
&lt;p&gt;A. Ferone, L. Maddalena, Neural Background Subtraction for Pan-Tilt-Zoom Cameras. &lt;strong&gt;IEEE Trans. Systems, Man, and Cybernetics: Systems&lt;/strong&gt; 44(5): 571-579 (2014)&lt;/p&gt;
&lt;p&gt;L. Maddalena, A. Petrosino, The 3dSOBS+ algorithm for moving object detection. &lt;strong&gt;Computer Vision and Image Understanding&lt;/strong&gt; 122: 65-73 (2014)&lt;/p&gt;
&lt;p&gt;A. Maratea, A. Petrosino, M. Manzo, Adjusted F-measure and kernel scaling for imbalanced data learning. &lt;strong&gt;Informaiton Sciences&lt;/strong&gt; 257: 331-341 (2014)&lt;/p&gt;
&lt;p&gt;L. Maddalena, A. Petrosino, F. Russo, People counting by learning their appearance in a multi-view camera environment. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 36: 125-134 (2014)&lt;/p&gt;
&lt;p&gt;A. Albanese, S. K. Pal, A. Petrosino, Rough Sets, Kernel Set, and Spatiotemporal Outlier Detection. &lt;strong&gt;IEEE Trans. Knowl. Data Eng.&lt;/strong&gt; 26(1): 194-207 (2014)&lt;/p&gt;
&lt;p&gt;A. Petrosino, S. K. Pal, Guest Editorial on Decision Making in Human and Machine Vision. &lt;strong&gt;IEEE Trans. Systems, Man, and Cybernetics: Systems&lt;/strong&gt; 44(5): 521-522 (2014)&lt;/p&gt;
&lt;p&gt;&lt;!-- raw HTML omitted --&gt;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. &lt;strong&gt;Ecological Informatics&lt;/strong&gt; 24: 186-193 (2014)&lt;!-- raw HTML omitted --&gt;&lt;/p&gt;
&lt;p&gt;V. Cantoni, A. Ferone, O. Ozbudak, A. Petrosino, Protein motifs retrieval by SS terns occurrences, &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 34(5): 559-563 (2013) - &lt;a href=&#34;/pdf/Protein.pdf&#34;&gt;PDF&lt;/a&gt; - &lt;a href=&#34;/bib/Protein.bib&#34;&gt;BibTeX&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;R. Melfi, S. Kondra, A. Petrosino, Human activity modeling by spatio temporal textural appearance. &lt;strong&gt;Pattern Recognition Letters&lt;/strong&gt; 34(15): 1990-1994 (2013)&lt;/p&gt;
&lt;p&gt;L. Maddalena, A. Petrosino, Stopped Object Detection by Learning Foreground Model in Videos. &lt;strong&gt;IEEE Trans. Neural Netw. Learning Syst.&lt;/strong&gt; 24(5): 723-735 (2013)&lt;/p&gt;
&lt;p&gt;F. Camastra, A. Ciaramella, A. Staiano, Machine learning and soft computing for ICT security: an overview of current trends. &lt;strong&gt;J. Ambient Intelligence and Humanized Computing&lt;/strong&gt; 4(2): 235-247 (2013)&lt;/p&gt;
&lt;p&gt;L. Lamberti, F. Camastra, Handy: A real-time three color glove-based gesture recognizer with learning vector quantization, &lt;strong&gt;Expert Syst. Appl.&lt;/strong&gt; 39(12): 10489-10494 (2012) - &lt;a href=&#34;/pdf/esa11_rev.pdf&#34;&gt;PDF&lt;/a&gt; - &lt;a href=&#34;/bib/esa11_rev.bib&#34;&gt;BibTex&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;A. Ferone, L. Maddalena, Neural Background Subtraction for PTZ Cameras, &lt;strong&gt;IEEE Transactions on Systems, Man, and Cybernetics: Systems&lt;/strong&gt;, accepted - [PDF](/pdf/Neural Background Subtraction for PTZ Cameras.pdf) - BibTeX&lt;/p&gt;
&lt;p&gt;A. Albanese, S. K. Pal, A. Petrosino, Rough Sets, Kernel Set and Spatio-Temporal Outlier Detection, &lt;strong&gt;IEEE Transactions on Knowledge and Data Engineering(99)&lt;/strong&gt;: 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)&lt;/p&gt;
&lt;p&gt;A. Petrosino, M. Miralto, A. Ferone, A real-time streaming server in the RTLinux environment using VideoLanClient, &lt;strong&gt;J. Real-Time Image Processing 6&lt;/strong&gt;(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)&lt;/p&gt;
&lt;p&gt;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) - &lt;a href=&#34;JSIP20110300017_53298522.pdf&#34;&gt;PDF&lt;/a&gt; - &lt;a href=&#34;/bib/JSIP20110300017_53298522.bib&#34;&gt;BibTeX&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;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)&lt;/p&gt;
&lt;p&gt;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) - &lt;a href=&#34;/pdf/2010_therapy.pdf&#34;&gt;PDF&lt;/a&gt; - &lt;a href=&#34;/bib/2010_therapy.bib&#34;&gt;BibTeX&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;L. Maddalena, A. Petrosino, &amp;ldquo;A Fuzzy Spatial Coherence-based Approach to Background/ Foreground Separation for Moving Object Detection&amp;rdquo;, Neural Computing and Applications19(2):179-186, (2010) - PDF - BibTeX&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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: &lt;a href=&#34;http://dx.doi.org/&#34;&gt;http://dx.doi.org/&lt;/a&gt; 10.1166/ jctn.2005.006, 2005;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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 &amp;amp; Astrophysics Journal, vol. 419, pp.485-500, ISSN: 0004-6361, doi:10.1051/0004-6361:20035771, 2004;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
&lt;p&gt;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;&lt;/p&gt;
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