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Ceccarelli, M., A. Petrosino, and R. Vaccaro, "Competitive Neural Networks on Message Passing Parallel Computers", Concurrency: Practice and Experience, vol. 5, no. 6, pp. 449-470, 1993.
Antoniol, G., and M. Ceccarelli, "A Computational Intelligence Approach to Unsupervised Microarray Image Gridding", Bioinformatics Italy 2004: BITS, 2004.
Ceccarelli, M., D. Grimaldi, F.. Lamonaca, and A. Speranza, "A Computer Vision Approach to Micro-Nucleous automatic detection and surface measurement", IEEE Medical Measurements 2009: IEEE, pp. 166-171, 2009.
Ceccarelli, M., D. Grimaldi, F.. Lamonaca, and G. Speranza, "Computer Vision Approach to Micro-Nucleus automatic detection and surface measurements", Proceeedings of IMEKO 2008, 2008.
Ceccarelli, M., F. Musacchia, and A. Petrosino, "Content-based Image Retrieval by a Fuzzy Scale-space Approach", International Journal Pattern Recognition and Artificial Intelligence, vol. 20, pp. 849-868, 2006.
Ceccarelli, M., and A. Petrosino, "Convergence and Processing in Learning for Neural Nets. The AAM Model", Parallel Architecture and Neural Networks '98: World Scientific Publishing, pp. 101-106, 1990.
Lisboa, P., A. Vellido, R. Tagliaferri, F. Napolitano, M. Ceccarelli, J. Martin-Guerrero, and E. Biganzoli, "Data Mining in Cancer Research", IEEE Computational Intelligence Magazine, vol. 5, no. 1, pp. 14-18, 2010.
Ceccarelli, M., L. Cerulo, and A. Santone, "De novo reconstruction of gene regulatory networks from time series data an approach based on formal methods", METHODS, vol. 69, pp. 298–305, 2014.
Diodato, N., M. Ceccarelli, and G. Bellocchi, "Decadal and century-long changes in the reconstruction of erosive rainfall anomalies in a Mediterranean fluvial basin", Earth Surface Processes and Landforms, vol. 33, no. 13, pp. 2078-2093, 2008.
Ceccarelli, M., V. De Simone, and A. Murli, "Decoupled Anisotropic Diffusion for Image Denoising", Proceed. of IASTED Int. Conf. on Signal and Image Processing: Acta Press, pp. 344-349, 1998.
Ceccarelli, M., and M. Donatiello, "A Deformable Grid Approach for Bayesian Image Registration", Signal Processing, Pattern Recognition, and Applications 2008: IASTED, 2008.
Ceccarelli, M., and G. Antoniol, "A Deformable Grid-Matching Approach for Microarray Images", IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 3178-3188, 2006.
Ceccarelli, M., and A. Petrosino, "Design of Robust RBF Classifiers for remote Sensing Data Analysi", Proceed. of IEEE International Conference on Neural Network 96: IEEE Press, 1996.
Noviello, T. M. R., A. Di Liddo, G. M. Ventola, A. Spagnuolo, S. D'Aniello, M. Ceccarelli, and L. Cerulo, "Detection of long non-coding RNA homology, a comparative study on alignment and alignment-free metrics", BMC BIOINFORMATICS, vol. 19, 2018.
Calabrese, G., M. Ceccarelli, L. Di Dio, G.. Papa, and R. Tagliaferri, "DIACONEA: On-Line Diagnois for a Complex Operating Environment: A Neural Approach", WIRN 1993: World Scientific Publishing, pp. 365-370, 1993.
Ceccarelli, M., and J. Hounsou, "A Dynamic Mixture of Gaussians Neural Network for Sequence Classification", Proceedings of CARI 1998: INRIA, pp. 817-823, 1998.
Ceccarelli, M., and J. T. Hounsou, "A Dynamic Mixture of Gaussians Neural Network for Sequence Recognition", Artificial Neural Networks IV: Springer Verlag, pp. 475-478, 1994.
Ceccarelli, M., A. Petrosino, and R. Tagliaferri, "Dynamics and Associative Mapping in Additive Systems", Proceedings of ICNN-1990 Paris: Kluwer Academic Publishers, pp. 986, 1990.
Ceccarelli, M., L. Cerulo, G. Canfora, and M. Di Penta, "An eclectic approach for change impact analysis", Proceedings - International Conference on Software Engineering, vol. 2, 2010.
Pagnotta, S. M., L. Carmelo, M. Pancione, L. Cerulo, V. Colantuoni, and M. Ceccarelli, "An Ensemble Greedy Algorithm for Feature Selection in Cancer Genomics", 5th International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA), 2011.
Diodato, N., and M. Ceccarelli, "Environinformatics in ecological risk assessment of agroecosystems pollutant leaching", Stochastic Environmental Research and Risk Assessment, vol. 19, no. 4, pp. 292-300, 2005.
Malta, T., T. Sabedot, M. Ceccarelli, F. Barthel, S. M. Pagnotta, A. Iavarone, R. Verhaak, TCGA. L. G. G. - G. B. M. wo group, and H. Noushmehr, "EPIG-14EPIGENOMIC (DNA METHYLATION AND EXPRESSION) SIGNATURES DEFINE SUBSETS OF BOTH IDHmut AND IDHwt GLIOMA WITH DISTINCT CLINICAL OUTCOMES", Neuro-Oncology, vol. 17, no. suppl 5, pp. v89, 2015.
De Stasio, A., M. Ertelt, W. Kemmner, U. Leser, and M. Ceccarelli, "Exploiting scientific workflows for large-scale gene expression data analysis", Proceedings of IEEE Int. Sym. on Computer and Information Sciences, 2009.: IEEE, pp. 448–453, 2009.
Ceccarelli, M., "Fast Edge Preserving Picture Recovery by Finite Markov Random Fields", Lecture Notes in Computer Science, vol. 3617, pp. 277-286, 2005.
Ceccarelli, M., "A Finite Markov Random Field approach to fast edge-preserving image recovery", Image and Vision Computing, vol. 25, no. 6, pp. 792-804, 2007.