[1] M. Anghinolfi, G. Ricco, P.
Corvisiero, and F. Masulli, The response of organic scintillators
to fast neutrons , Nucl. Instr. Meth., vol. 165, pp. 217-224, 1979 (
pdf).
[2] M. Scotto, P. G. Gagna, M. Nobile, L. Spadavecchia, and F.
Masulli, Computer assisted generation of time-compressed video
signals for visual studies, IEEE Trans. Biomedical Engineering, vol. 35
(3), pp. 210-214, 1988 (
pdf).
[3] F. Masulli and M. Riani, Ambiguity and structural information
in the perception of reversible figures, Perception &
Psychophysics, vol. 45 (6), pp. 501-513, 1989 (
pdf).
[4] F. Masulli, D. Sona, A. Sperduti, A Starita, and G.
Zaccagnini, A system for the automatic morphological analysis of
mediaeval manuscripts, Journal of Forensic Document Examination, vol.
9, pp. 45-55, 1996, (invited) (
pdf).
5] A. Schenone, F. Firenze, F. Acquarone, M. Gambaro, F. Masulli, and
L. Andreucci, Segmentation of multivariate medical images via
unsupervised clustering with adaptive resolution, Computerized Medical
Imaging and Graphics, vol. 20, pp. 119-129, 1996 (
pdf).
[6] L. Studer and F. Masulli, Building a neuro-fuzzy system to
efficiently forecast chaotic time series, Nuclear Instruments and
Methods in Physics Research, Section A, vol. 389, pp. 264-667, 1997 (
pdf).
[7] F. Casalino, F. Masulli, and A. Sperduti, Rule specialization
in networks of fuzzy basis functions, Intelligent Automation and Soft
Computing, vol. 4, pp. 73-82, 1998 (
pdf).
[8] P. Bogus, A. M. Massone, F. Masulli, and A. Schenone,
Interactive graphical system for the segmentation of multimodal medical
volumes using fuzzy clustering, Machine Graphics & Vision, vol. 7,
pp. 781-791, ISSN 1230-0535, 1998 (
pdf).
[9] P. Gurzi, A. Masulli, Spalvieri, M. L. Sotgiu, and G. Biella,
Rough annealing by two-step clustering, with application to neuronal
signals, Journal of Neuroscience Methods, vol 85(1), pp. 81-87, 1998 (
pdf).
[10] A. Zucchiatti, D. Moricciani, A. M. Massone, F. Masulli, M.
Copogni, M. Castoldi, A. D Angelo, F. Ghio, B. Girolami, P. Levi
Sandri, and M. Sanzone, Optimization of clustering algorithms for
the reconstruction of events started by a 1 GeV photon beam in a
segmentated BGO calorimeter, Nuclear Instruments and Methods in Physics
Research, Section A, vol. 425, pp. 536-548, 1999 (
pdf).
[11] F. Masulli and A. Schenone, A fuzzy clustering based
segmentation system as support to diagnosis in medical imaging,
Artificial Intelligence in Medicine, vol. 16, pp. 129-147, 1999 (
pdf).
[12] F. Masulli, R. Parenti, and L. Studer, Neural modeling of
non-linear processes: Relevance of the Takens-Mane theorem,
International Journal on Chaos Theory and Applications, ISSN 1453-1437,
Vol. 4/2-3, pp. 59-74, 1999 (
pdf).
[13] M. Pardo, G. Faglia, G. Sberveglieri, M. Corte, F. Masulli, and M.
Riani, A time delay neural network for estimation of gas
concentrations in a mixture, Sensors and Actuators B, vol. 65/1-3, pp.
267-269, 2000 (
pdf).
[14] M. Pardo, G. Faglia, G. Sberveglieri, M. Corte, F. Masulli, and M.
Riani, Monitoring reliability of sensors in an array by neural
networks, Sensors and Actuators B, vol. 67, pp. 128-133, 2000 (
pdf).
[15] Gb. Cicioni and F. Masulli, and D. Baratta, A software
toolbox for time series prediction and its application to daily
rainfall forecasting in a geographic basin, Economics and Complexity,
vol. 2 n.1, pp. 11-24, 2000, ISSN. 1398-1706, (invited) (
pdf).
[16] R. Parenti, C. Penno, D. Baratta and F. Masulli,
Implementing very high Speed hierarchical MLP-based Classification
Systems in real-time industrial environments, KES - International
Journal of Knowledge-Based Intelligent Engineering Systems, vol. 5, pp.
179-186, 2001 (
pdf).
[17] M. Pardo, G. Sberveglieri, F. Masulli, and G. Valentini,
Decompositive Classification Models for Electronic Noses, Analitica
Chimica Acta, vol. 446, pp. 223 232, 2001 (
pdf).
[18] N. Giusti, F. Masulli and A. Sperduti, Theoretical and
Experimental Analysis of a Two-Stage System for Classification, IEEE
Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no.
7, pp. 893-904, 2002 (
pdf).
[19] G Valentini and F. Masulli, NEURObjects: an object-oriented
library for neural network development, Neurocomputing, vol. 48 no 1/4,
pp. 623-646, 2002 (
pdf).
[20] D. Baratta, Gb. Cicioni, F. Masulli, L. Studer, Application
of an Ensemble Technique based on Singular Spectrum Analysis to Daily
Rainfall Forecasting, Neural Networks, vol. 16/3-4, pp.375-387, 2003 (
pdf).
[21] F. Masulli, S. Rovetta, Random Voronoi ensembles for gene
selection, Neurocomputing, vol. 55/3-4, pp. 721 726, 2003 (
pdf).
[22] P. Rosso, F. Masulli, D. Buscaldi, Un Metodo Automatico para
la Desambiguacion Lexica de Nombres, Revista Colombiana de Computacion,
Vol.4/1, pp.57-64, ISSN 1657 2831, 2003 (
pdf).
[23] F. Masulli, F. and G. Valentini, Effectiveness of Error
Correction Output coding decomposition Schemes in ensemble and
monolithic learning machines, Pattern Analysis and Application Journal,
vol. 6, pp. 285-300, 2003 (
pdf).
[24] F. Masulli, G. Valentini, An experimental analysis of the
dependence among codeword bit errors in ECOC learning machines,
Neurocomputing, 57C, pp. 189-214, 2004 (
pdf).
[25] G.B. Ferrara, L. Delfino, F. Masulli, S. Rovetta, R. Sensi,
A Fuzzy Approach to Image Analysis in HLA Typing using Oligonucleotide
Microarrays, Fuzzy Sets and Systems, 152, pp. 37-48, 2005 (
pdf).
[26] S. Rovetta, F. Masulli, Fuzzy concepts in vector
quantization training, Image and Vision Computing (in press) (
pdf).
[27] F. Masulli and G. Valentini, Effectiveness of error
correcting output correcting output codes in multiclass learning
problems, in Proceedings of MCS2000 - First International Workshop on
Multiple Classifier Systems, Cagliari (Italy), June 21-23, 2000,
Lecture Notes in Computer Science, pp. 107-116, vol 1857,
Springer-Verlag, Heidelberg (Germany) (
pdf).
[28] F. Masulli, and G. Valentini, Dependence among Codewords
Bits Errors in ECOC learning Machines: An Experimental Analysis, in
MCS2001 International Workshop on Multiple Classifier Systems, pp. 158
167, Lecture Notes in Computer Sciences, Vol. 1857, Springer-Verlag,
Heidelberg (Germany), 2001 (
pdf).
[29] F. Masulli, M. Pardo, G. Sberveglieri, G. Valentini,
Boosting Classifiers in Electronic Noses, in MCS2002, Multiple
Classifier Systems, Series Lecture Notes in Computer Sciences, Vol.
2364, pp. 262-271, Springer-Verlag, Heidelberg (Germany), 2002 (
pdf).
[30] G. Valentini and F. Masulli, Ensembles of Learning Machines,
in M. Marinaro and R. Tagliaferri, editors, Neural Nets WIRN Vietri-02,
Series Lecture Notes in Computer Sciences, Vol. 2486, pp.3 19,
Springer-Verlag, Heidelberg (Germany), 2002 (invited review) (
pdf).
[31] P. Rosso, F. Masulli, D. Buscaldi, F. Pla, and A.G. Molina,
Automatic Noun Disambiguation, in A. Gelbukh, editor, Computational
Linguistics and Intelligent Text Processing 4th International
Conference, CICLing 2003, Mexico City, Mexico, Series Lecture Notes in
Computer Sciences,Vol. 2588, pp.273-276, Springer-Verlag, Heidelberg
(Germany), 2003 (
pdf).
[32] F. Masulli, S. Rovetta, An Algorithm to Model Paradigm
Shifting in Fuzzy Clustering, in B. Apolloni, M. Marinaro, R.
Tagliaferri, editors, Neural Nets Wirn Vietri-03, Series Lecture Notes
in Computer Sciences,Springer-Verlag, Heidelberg (Germany), Vol. 2859,
pp.70-76, Springer-Verlag, Heidelberg (Germany), 2003 (
pdf).
[33] F. Masulli, S. Rovetta, Gene selection using Random Voronoi
Ensembles, in B. Apolloni, M. Marinaro, R. Tagliaferri, editors, Neural
Nets Wirn Vietri-03, Series Lecture Notes in Computer Sciences,
Springer-Verlag, Heidelberg (Germany), Vol. 2859, pp. 302-307,
Springer-Verlag, Heidelberg (Germany), 2003 (
pdf).
[34] F. Masulli, S. Rovetta, Fuzzy concepts in vector
quantization training, in V. Di Gesu, F. Masulli, A. Petrosino,
editors, WILF03 - International Workshop on Fuzzy Logic and
Applications, Series Lecture Notes in Computer Sciences,
Springer-Verlag, Heidelberg (Germany), Springer-Verlag, Heidelberg
(Germany), in press (
pdf).
[35] D. Buscaldi, P. Rosso, F. Masulli, Integrating Conceptual
Density with WordNet Domain and CALD Glosses for Noum Sense
Disambiguation, Advances in Natural Language Processing: 4th
International Conference, EsTAL 2004, Alicante, Spain, October 20-22,
2004, Series Lecture Notes in Computer Sciences, vol. 3230, pp.
183-194, Springer-Verlag, Heidelberg (Germany), 2004 (
pdf).
[36] F. Masulli, Bayesian classification by feedforward
connectionist systems, in F. Masulli, P. G. Morasso, and A. Schenone,
editors, Neural Networks in Biomedicine - Proceedings of the Advanced
School of the Italian Biomedical Physics Association - Como (Italy)
1993, pp. 145-162, Singapore, 1994. World Scientific (
pdf).
[37] F. Masulli, A. M. Massone, and A. Schenone, Fuzzy clustering
methods for the segmentation of multimodal medical volumes, in P. S.
Szczepaniak, P. J. G. Lisboa, and S. Tsumoto, editors, Fuzzy Systems in
Medicine. Series Studies in Fuzziness and Soft Computing, editor J.
Kacprzyk, Springer-Verlag, pp. 335-350, Heidelberg (Germany), 2000,
(invited) (
pdf).
[38] F. Masulli and A. Sperduti, Learning techniques for
supervised fuzzy classifiers, in, L. K. Jain and M. Russo, editors,
Fuzzy Learning, pp. 147-169 CRC Press, Cambridge, 2000, (invited) (
pdf).
[39] F. Masulli and S. Rovetta, Metodi Non Supervisionati
nell'Analisi Esplorativa di Dati da DNA Microarray, in M. Ceccarelli,
editor, Metodi Computazionali per la Bioinformatica, Franco Angeli,
Italy, (invited), in press (
pdf).
[40] F. Masulli and F. Casalino, A neuro-fuzzy system for
Bayesian classification, in Proceedings of EUFIT 95 Third European
Congress on Intelligent Techniques and Soft Computing, pp. 1425 1429,
Aachen (Germany), 1995. Verlag und Druck Mainz. (invited at the session
on Fuzzy Classification Rules) (
pdf).
[41] F. Firenze, A. Schenone, F. Acquarone, M. Gambaro, and F.
Masulli, Adaptive resolution analysis of multivariate medical
images via unsupervised neural network based clustering, in Proceedings
of EUFIT 95 Third European Congress on Intelligent Techniques and Soft
Computing, pp. 1690-1694, Aachen (Germany), 1995. Verlag und Druck
Mainz. (invited at the session on Image Processing by Soft Computing)
(
pdf).
[42] F. Masulli, A. Sperduti, and D. Alfonso, A hybrid pattern
recognition scheme, in B. Bosacchi and J. Bezdek, editors, Applications
of Fuzzy Logic Technology III - SPIE Proceedings Series, vol. 2761, pp.
154-162, Orlando, Florida, 1996. SPIE - Bellingam, WA, USA. (invited
paper) (
pdf).
[43] A. Schenone, F. Masulli, and M. Artuso, A neural bootstrap
for the Possibilistic C-Mean algorithm, in F. C. Morabito, editor,
Advances in Intelligent Systems, pp. 359-366, Amsterdam, 1997. IOS
Press, (invited paper at the International Symposium on Intelligent
Systems AMSE-ISIS 97, Reggio Calabria, Italy, September 11-13, 1997)
(
pdf).
[44] F. Masulli and L. Studer, Neuro-fuzzy system for chaotic
time series forecasting, in B. Bosacchi, J. C. Bezdek, and D. B. Fogel,
editors, Applications of Soft Computing - SPIE Proceedings Series, vol.
3165, pp. 205-215, San Diego, CA, 1997. SPIE - Bellingam, WA, USA,
(invited paper) (
pdf).
[45] Gb. Cicioni and F. Masulli, Computational intelligence in
hydroinformatics: A review, in M. Marinaro and R. Tagliaferri, editors,
Neural Nets WIRN Vietri-99, pp. 41-59, London, 1999. Springer, (invited
review) (
pdf).
[46] F. Masulli, M. Riani, and E. Simonotto, A multilayer neural
network modelling the perceptual reversal of ambiguous patterns, in M.
Caudill, editor, Proceedings of the International Joint Conference on
Neural Networks, Washington D. C., 1990 (IJCNN-90-WASH-DC), vol. 1, pp.
185-188, Hillsdale, 1990. Lawrence Erlbaum Associated Inc (
pdf).
[47] R. Battiti and F. Masulli, BFGS optimization for faster and
automated supervised learning, in B. Widrow and B. Angeniol, editors,
International Neural Network Conference, INNC 90 PARIS (International
Neural Network Society and IEEE), vol. 2, pp. 757-760, Dordrecht, 1990.
Kluwer Academic Publishers (
pdf).
[48] M. Riani and F. Masulli, Stochastic dynamics and input
dimensionality in a two-layer neuronal network for modelling
multistable perception, in B. Widrow and B. Angeniol, editors,
International Neural Network Conference, INNC 90 PARIS (International
Neural Network Society and IEEE), vol. 2, pp. 1019-1022, Dordrecht,
1990. Kluwer Academic Publishers (
pdf).
[49] M. Riani, F. Masulli, and E. Simonotto, Perceptual
alternation of ambiguous patterns: A model based on an artificial
neural network, in S. K. Roger, editor, Application of Artificial
Neural Networks II - SPIE Proceedings Series, vol. 1469, pp. 166-177,
Orlando, Florida, 1991. SPIE - Bellingam, WA, USA (
pdf).
[50] F. Masulli, M. Riani, E. Simonotto, and F. Vannucci,
Boltzmann distributions and neural networks: Models of unbalanced
interpretations of reversible patterns, in D. W. Ruck, editor, Science
of Artificial Neural Networks- SPIE Proceedings Series, vol. 1710, pp.
267-277, Orlando, Florida, 1992. SPIE - Bellingam, WA, USA (
pdf).
[51] F. Masulli, F. Casalino, and F. Vannucci, Bayesian
properties and performances of adaptive fuzzy systems in pattern
recognition problems, in M. Marinaro and P. G. Morasso, editors,
Proceedings of the European Conference on Artificial Neural Networks,
ICANN-94, pp. 189-192, Sorrento, Italy, 1994. Springer (
pdf).
[52] F. Casalino, F. Masulli, A. Sperduti, and F. Vannucci,
Semantic phase transition in a classifier based on an adaptive fuzzy
system, in Proceedings of the Third IEEE International Conference on
Fuzzy Systems, IEEE-FUZZ94, vol. 2, pp. 808-812, Orlando, FL, USA,
1994. IEEE (
pdf).
[53] F. Masulli and M. Penna, Improving learning speed and
generalization in multi-layer perceptrons through principal component
analysis, in S. K Roger and D. W. Ruck, editors, Applications and
Science of Artificial Neural Networks II - SPIE Proceedings Series,
vol. 2790, pp. 85-95, Orlando, Florida, 1996. SPIE - Bellingam, WA,
USA (
pdf).
[54] M. Castellano, F. Masulli, and M. Penna, Fuzzy systems in
High Energy Physics, in B. Bosacchi and J. Bezdek, editors,
Applications of Fuzzy Logic Technology III - SPIE Proceedings Series,
vol. 2761, pp. 162-171, Orlando, Florida, 1996. SPIE - Bellingam, WA,
USA (
pdf).
[55] F. Masulli, P. Bogus, A. Schenone, and M. Artuso, Fuzzy
clustering methods for the segmentation of multivariate images, in M.
Mares, R. Mesia, V. Novak, J. Ramik, and A. Stupnanova, editors,
Proceedings of the 7th International Fuzzy Systems Association Word
Congress IFSA 97, vol. III, pp. 123-128, Prague, 1997. Academia (
pdf).
[56] N. Giusti, F. Masulli, and A. Sperduti, Competitive and
hybrid neuro-fuzzy models for supervised classification, in Proceedings
of 1997 IEEE International Conference on Neural Networks, INNC 97, pp.
516-519, Huston, USA, 1997. IEEE (
pdf).
[57] F. Masulli and G. Valentini, Parallel non linear
dichotomizers, in Proceedings of IJCNN 20000, The IEEE-INNS-ENNS Int.
Joint Conf. on Neural Networks, pp. 29-33, IEEE, Piscataway, NJ, USA,
2000 (
pdf).
[58] F. Masulli and G. Valentini, Comparing Decomposition Methods
for Classification, in Proceedings of KES 2000-International Conference
on Knowledge-Based Intelligent Engineering Systems and Allied
Technologies, vol. 2, pp. 788-792, IEEE, Piscataway, NJ, USA, 2000
(
pdf).
[59] A. M. Massone, L. Studer, F. Masulli, and G. Valentini,
Pattern Recognition in RICH Counters Using the Possibilistic
C-Spherical Shell Algorithm, in Proceedings of KES 2000-International
Conference on Knowledge- Based Intelligent Engineering Systems and
Allied Technologies, vol. 2, pp. 791-795, IEEE, Piscataway, NJ, USA
(
pdf).
[60] F. Masulli, and G. Valentini, Quantitative Evaluation of
Dependence among Outputs in ECOC Classifiers Using Mutual Information
Based Measures, in Proceedings of the International Joint Conference on
Neural Networks IJCNN 01, pp. 784-789, vol. 2, IEEE, Piscataway, NJ,
USA, 2001 (
pdf).
[61] F. Masulli, D. Baratta, Gb. Cicioni, Gb. and L. Studer,
Daily Rainfall Forecasting using an Ensemble Technique based on
Singular Spectrum Analysis, in Proceedings of the International Joint
Conference on Neural Networks IJCNN 01, pp. 263-268, vol. 1, IEEE,
Piscataway, NJ, USA, 2001 (
pdf).
[62] F. Beltrame, G. DeLeo, M. Fato, F. Masulli, and A. Schenone,
Threedimensional visualizzaztion and navigation tool for disgnostic and
surgical planning applications, in Proceedings of SPIE - Medical
Imaging 2001 - Visualizzation, Display and Image-Guided Procedure, pp.
507-514, vol. 4319, SPIE, Bellingam, Washington, USA, 2001 (
pdf).
[63] F. Masulli, and S. Rovetta, An ensemble approach to variable
selection for classification of DNA microarray data in Proceedings of
the International Joint Conference on Neural Networks IJCNN 03,
Portland, Oregon, M. Hasselmo (Editor) pp. 3089-3094, IEEE Neural
Network Society, Piscataway, NJ, USA, 2003 (
pdf).
[64] F. Masulli, and S. Rovetta, The Graded Possibilistic
Clustering Model in Proceedings of the International Joint Conference
on Neural Networks IJCNN 03, Portland, Oregon, M. Hasselmo (Editor) pp.
791-796, IEEE Neural Network Society, Piscataway, NJ, USA, 2003 (
pdf).
[65] F. Masulli, and S. Rovetta, HLA Typing Using a Fuzzy
Approach in Proceedings of the International Joint Conference on Neural
Networks IJCNN 04, Budapest, Hungary, pp. 3235-3240, IEEE Neural
Network Society, Piscataway, NJ, USA, 2004 (
pdf).
[66] D. Buscaldi, P. Rosso, and F. Masulli, The
upv-unige-CIAOSENSO WSD system in Rada Mihalcea and Phil Edmonds
(Ed.s), Senseval-3: Third International Workshop on the Evaluation of
Systems for the Semantic Analysis of Text, pp. 77-82, Association for
Computational Linguistics, Barcelona, Spain, 2004 (
pdf).
[67] F. Masulli, S. Rovetta, A New Approach to Hierarchical
Clustering for the Analysis of Genomic Data Proceedings of the
International Joint Conference on Neural Networks 2005, Montreal -
Canada, IEEE Computational Intelligence Society, Piscataway, NJ, USA
(in press) (
pdf).
Francesco Masulli