Journal Papers

Alessio Ferone, Antonio Maratea: Integrating rough set principles in the graded possibilistic clustering. Information Sciences. 477: 148-160 (2019)

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. Ecological Informatics 49: 54-61 (2019)

Silvio Barra, Maria De Marsico, Michele Nappi, Fabio Narducci, Daniel Riccio: A hand-based biometric system in visible light for mobile environments. Information Sciences. 479: 472-485 (2019)

Battistone, Francesco, Alfredo Petrosino: TGLSTM: A time based graph deep learning approach to gait recognition. Pattern Recognition Letters (in press).

Freire-Obregón, D., Narducci, F., Barra, S., Castrillón-Santana, M.: Deep learning for source camera identification on mobile devices. Pattern Recognition Letters (in press)

L. Maddalena and A. Petrosino, Self-Organizing Background Subtraction Using Color and Depth Data, Multimedia Tools and Applications, Springer, (in press).

Francesco Battistone, Alfredo Petrosino, Vincenzo Santopietro, Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles. Signal Processing Systems 90(6): 891-900 (2018)

Francesco Camastra, Francesco Esposito, Antonino 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)

Alessio Ferone: Feature selection based on composition of rough sets induced by feature granulation. Internatioanl Journal Approximate Reasoning 101: 276-292 (2018)

Silvio Barra, Kim-Kwang Raymond Choo, Michele Nappi, Arcangelo Castiglione, Fabio Narducci, Rajiv Ranjan: Biometrics-as-a-Service: Cloud-Based Technology, Systems, and Applications. IEEE Cloud Computing 5(4): 33-37 (2018)

Maria De Marsico, Michele Nappi, Fabio Narducci, Hugo Proença: Insights into the results of MICHE I - Mobile Iris CHallenge Evaluation. Pattern Recognition 74: 286-304 (2018)

Alfredo Petrosino, Lucia Maddalena, Thierry Bouwmans: Editorial-Scene background modeling and initialization. Pattern Recognition Letters 96: 1-2 (2017)

Thierry Bouwmans, Lucia Maddalena, Alfredo Petrosino: Scene background initialization: A taxonomy. Pattern Recognition Letters 96: 3-11 (2017)

Jodoin P-M, Maddalena L., Petrosino A., Wang Y., Extensive Benchmark and Survey of Background Modeling Methods. IEEE Transactions on Image Processing 26 (11) : 5244-5256 (2017)

Aniello Castiglione, Kim-Kwang Raymond Choo, Michele Nappi, Fabio Narducci: Biometrics in the Cloud: Challenges and Research Opportunities. IEEE Cloud Computing 4(4): 12-17 (2017)

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. Pattern Recognition Letters 91: 37-43 (2017)

F. Camastra, A. Staiano, Intrinsic dimension estimation: Advances and open problems. Information Sciences. 328: 26-41 (2016)

M. De Marsico, A. Petrosino, S. Ricciardi, Iris recognition through machine learning techniques: A survey. Pattern Recognition Letters 82: 106-115 (2016)

Angelo Ciaramella, Giulio Giunta: Packet loss recovery in audio multimedia streaming by using compressive sensing. IET Communications 10(4): 387-392 (2016)

Angelo Ciaramella, Marco Gianfico, Giulio Giunta: Compressive sampling and adaptive dictionary learning for the packet loss recovery in audio multimedia streaming. Multimedia Tools Appl. 75(24): 17375-17392 (2016)

João C. Neves, Fabio Narducci, Silvio Barra, Hugo Proença: Biometric recognition in surveillance scenarios: a survey. Artificial Intelligence Review 46(4): 515-541 (2016)

Fabio Narducci, Stefano Ricciardi, Raffaele Vertucci: Enabling consistent hand-based interaction in mixed reality by occlusions handling. Multimedia Tools Appl. 75(16): 9549-9562 (2016)

A. Petrosino, Special Section: ICIAP 2013 Awards. Pattern Recognition Letters 55: 34 (2015)

F. Camastra, R. Amato, M. D. Di Taranto, A. Staiano, Advances in Computational Methods for Genetic Diseases. Comp. Math. Methods in Medicine 2015: 645649:1-645649:2 (2015)

F. Camastra, M. D. Di Taranto, A. Staiano, Statistical and Computational Methods for Genetic Diseases: An Overview. Comp. Math. Methods in Medicine 2015: 954598:1-954598:8 (2015)

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. Expert Syst. Appl. 42(3): 1710-1716 (2015)

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. Expert Syst. Appl. 42(3): 1710-1716 (2015)

Silvio Barra, Andrea Casanova, Fabio Narducci, Stefano Ricciardi: Ubiquitous iris recognition by means of mobile devices. Pattern Recognition Letters 57: 66-73 (2015)

L. Maddalena, A. Petrosino, The 3dSOBS+ algorithm for moving object detection. Computer Vision and Image Understanding 122: 65-73 (2014)

A. Maratea, A. Petrosino, M. Manzo, Adjusted F-measure and kernel scaling for imbalanced data learning. Informaiton Sciences 257: 331-341 (2014)

L. Maddalena, A. Petrosino, F. Russo, People counting by learning their appearance in a multi-view camera environment. Pattern Recognition Letters 36: 125-134 (2014)

A. Albanese, S. K. Pal, A. Petrosino, Rough Sets, Kernel Set, and Spatiotemporal Outlier Detection. IEEE Trans. Knowl. Data Eng. 26(1): 194-207 (2014)

A. Petrosino, S. K. Pal, Guest Editorial on Decision Making in Human and Machine Vision. IEEE Trans. Systems, Man, and Cybernetics: Systems 44(5): 521-522 (2014)

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. Ecological Informatics 24: 186-193 (2014)

R. Melfi, S. Kondra, A. Petrosino, Human activity modeling by spatio temporal textural appearance. Pattern Recognition Letters 34(15): 1990-1994 (2013)

L. Maddalena, A. Petrosino, Stopped Object Detection by Learning Foreground Model in Videos. IEEE Trans. Neural Netw. Learning Syst. 24(5): 723-735 (2013)

F. Camastra, A. Ciaramella, A. Staiano, Machine learning and soft computing for ICT security: an overview of current trends. J. Ambient Intelligence and Humanized Computing 4(2): 235-247 (2013)

A. Ferone, L. Maddalena, Neural Background Subtraction for PTZ Cameras, IEEE Transactions on Systems, Man, and Cybernetics: Systems, accepted - [PDF](/pdf/Neural Background Subtraction for PTZ Cameras.pdf) - BibTeX

A. Albanese, S. K. Pal, A. Petrosino, Rough Sets, Kernel Set and Spatio-Temporal Outlier Detection, IEEE Transactions on Knowledge and Data Engineering(99): 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)

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) - PDF - BibTeX

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) - PDF - BibTeX

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