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Antonino Staiano
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2020 – today
- 2024
- [j27]Vincenzo Mariano Scarrica
, Ciro Panariello, Alessio Ferone, Antonino Staiano
A hybrid approach to real-time multi-target tracking. Neural Comput. Appl. 36(17): 10055-10066 (2024) - [j26]Angelo Sozio, Vincenzo Mariano Scarrica, Angela Rizzo
Application of Direct and Indirect Methodologies for Beach Litter Detection in Coastal Environments. Remote. Sens. 16(19): 3617 (2024) - [c26]Vincenzo Mariano Scarrica, Antonino Staiano
Unveiling Graph Power: SegmentAnything and GCN Synergy for Instance Segmentation and Classification. EAIS 2024: 1-7 - [c25]Francesco Camastra, Angelo Ciaramella, Angelo Casolaro, Pasquale De Trino, Alessio Ferone, Giovanni Hauber, Gennaro Iannuzzo, Vincenzo Mariano Scarrica, Antonio Junior Spoleto, Antonino Staiano, Maria Concetta Vitale:
An integrated intelligent surveillance system for Industrial areas. Ital-IA 2024: 236-241 - [c24]Paola Barra, Francesco Camastra, Angelo Ciaramella, Ciro Giuseppe De Vita, Emanuel Di Nardo, Raffaele Montella, Gennaro Mellone, Vincenzo Scarrica, Antonino Staiano:
Safeguarding the Marine and Coastal Environment with Artificial Intelligence. Ital-IA 2024: 534-539 - 2023
- [c23]Francesco Camastra, Angelo Ciaramella, Emanuel Di Nardo, Alessio Ferone, Antonio Maratea, Raffaele Montella, Antonino Staiano:
AI-based Monitoring of Coastal and Marine Environments. Ital-IA 2023: 575-579 - [i4]Vincenzo Mariano Scarrica, Ciro Panariello, Alessio Ferone, Antonino Staiano:
A Hybrid Approach To Real-Time Multi-Object Tracking. CoRR abs/2308.01248 (2023) - [i3]Vincenzo Mariano Scarrica, Antonino Staiano
Learning Spatial Distribution of Long-Term Trackers Scores. CoRR abs/2308.01256 (2023) - 2022
- [j25]Vincenzo Mariano Scarrica, Pietro Patrizio Ciro Aucelli, Cosimo Cagnazzo, Angelo Casolaro, Pierpaolo Fiore, Marco La Salandra, Angela Rizzo, Giovanni Scardino, Giovanni Scicchitano, Antonino Staiano:
A novel beach litter analysis system based on UAV images and Convolutional Neural Networks. Ecol. Informatics 72: 101875 (2022) - [j24]Francesco Camastra
Prediction of environmental missing data time series by Support Vector Machine Regression and Correlation Dimension estimation. Environ. Model. Softw. 150: 105343 (2022) - [c22]Jhony H. Giraldo, Vincenzo Mariano Scarrica, Antonino Staiano
Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation. ICIP 2022: 16-20 - [i2]Jhony H. Giraldo, Vincenzo Mariano Scarrica, Antonino Staiano
Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation. CoRR abs/2210.05564 (2022) - 2021
- [j23]Paolo Cazzaniga, Maria Raposo
Selected papers from the 15th and 16th international conference on Computational Intelligence Methods for Bioinformatics and Biostatistics. BMC Bioinform. 22-S(2): 90 (2021) - [c21]Francesco Camastra, Angelo Ciaramella, Salvatore Sposato, Antonino Staiano:
A fuzzy rule base minimization perspective in XAI. WILF 2021 - 2020
- [j22]Angelo Ciaramella, Davide Nardone, Antonino Staiano
Data integration by fuzzy similarity-based hierarchical clustering. BMC Bioinform. 21-S(10): 350 (2020) - [j21]Le Hoang Son, Angelo Ciaramella, Duong Thi Thu Huyen, Antonino Staiano
Predictive reliability and validity of hospital cost analysis with dynamic neural network and genetic algorithm. Neural Comput. Appl. 32(18): 15237-15248 (2020) - [j20]Le Hoang Son, Angelo Ciaramella, Duong Thi Thu Huyen, Antonino Staiano
Correction to: Predictive reliability and validity of hospital cost analysis with dynamic neural network and genetic algorithm. Neural Comput. Appl. 32(23): 17807 (2020) - [c20]Francesco Camastra
Environmental Time Series Prediction with Missing Data by Machine Learning and Dynamics Recostruction. ICPR Workshops (6) 2020: 26-33 - [p6]Francesco Camastra
Semantic Maps for Knowledge Management of Web and Social Information. Computational Intelligence for Semantic Knowledge Management 2020: 39-51 - [p5]Angelo Ciaramella
Blind Source Separation Using Dictionary Learning in Wireless Sensor Network Scenario. Neural Approaches to Dynamics of Signal Exchanges 2020: 119-131 - [e1]Maria Raposo
Computational Intelligence Methods for Bioinformatics and Biostatistics - 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6-8, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11925, Springer 2020, ISBN 978-3-030-34584-6 [contents]
2010 – 2019
- 2019
- [j19]Angelo Ciaramella
On the Role of Clustering and Visualization Techniques in Gene Microarray Data. Algorithms 12(6): 123 (2019) - [j18]Elena Chianese, Francesco Camastra
Spatio-temporal learning in predicting ambient particulate matter concentration by multi-layer perceptron. Ecol. Informatics 49: 54-61 (2019) - [j17]Friedrich Recknagel, Antonino Staiano
Editorial: Analysis and synthesis of ecological data by machine learning. Ecol. Informatics 53 (2019) - [j16]Davide Nardone, Angelo Ciaramella, Antonino Staiano
A Sparse-Modeling Based Approach for Class Specific Feature Selection. PeerJ Comput. Sci. 5: e237 (2019) - [p4]Mario Iannicelli, Davide Nardone, Angelo Ciaramella
Content-Based Music Agglomeration by Sparse Modeling and Convolved Independent Component Analysis. Quantifying and Processing Biomedical and Behavioral Signals 2019: 87-96 - [i1]Davide Nardone, Angelo Ciaramella
A Sparse-Modeling based approach for Class-Specific feature selection. PeerJ Prepr. 7: e27740 (2019) - 2018
- [j15]Francesco Camastra
Linear SVM-based recognition of elementary juggling movements using correlation dimension of Euler Angles of a single arm. Neural Comput. Appl. 29(11): 1005-1013 (2018) - [c19]Angelo Ciaramella
Compressive Sensing and Hierarchical Clustering for Microarray Data with Missing Values. CIBB 2018: 3-10 - [c18]Francesco Camastra
Fuzzy Similarity-Based Hierarchical Clustering for Atmospheric Pollutants Prediction. WILF 2018: 123-133 - [p3]Francesco Camastra
Correlation Dimension-Based Recognition of Simple Juggling Movements. Multidisciplinary Approaches to Neural Computing 2018: 77-84 - 2017
- [c17]Antonino Staiano
An RBF neural network-based system for home smart metering. FUZZ-IEEE 2017: 1-6 - [c16]Francesco Camastra
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. ICANN (1) 2017: 407-414 - [c15]Daniele Davino, Francesco Camastra
Spam Detection by Machine Learning-Based Content Analysis. IIH-MSP (1) 2017: 415-422 - 2016
- [j14]Francesco Camastra
Intrinsic dimension estimation: Advances and open problems. Inf. Sci. 328: 26-41 (2016) - [p2]Angelo Ciaramella
A Bayesian-Based Neural Network Model for Solar Photovoltaic Power Forecasting. Advances in Neural Networks 2016: 169-177 - 2015
- [j13]Francesco Camastra
Advances in Computational Methods for Genetic Diseases. Comput. Math. Methods Medicine 2015: 645649:1-645649:2 (2015) - [j12]Francesco Camastra
Statistical and Computational Methods for Genetic Diseases: An Overview. Comput. Math. Methods Medicine 2015: 954598:1-954598:8 (2015) - [j11]Francesco Camastra
A fuzzy decision system for genetically modified plant environmental risk assessment using Mamdani inference. Expert Syst. Appl. 42(3): 1710-1716 (2015) - [p1]Francesco Camastra
Machine Learning-Based Web Documents Categorization by Semantic Graphs. Advances in Neural Networks 2015: 75-82 - 2014
- [j10]Francesco Camastra
TÉRA: A tool for the environmental risk assessment of genetically modified plants. Ecol. Informatics 24: 186-193 (2014) - 2013
- [j9]Francesco Camastra
Machine learning and soft computing for ICT security: an overview of current trends. J. Ambient Intell. Humaniz. Comput. 4(2): 235-247 (2013) - [c14]Francesco Camastra
Environmental Risk Assessment of Genetically Modified Organisms by a Fuzzy Decision Support System. ICIAP Workshops 2013: 428-435 - [c13]Francesco Camastra
Rule Learning in a Fuzzy Decision Support System for the Environmental Risk Assessment of GMOs. WILF 2013: 226-233 - [c12]Francesco Camastra
A Fuzzy Decision Support System for the Environmental Risk Assessment of Genetically Modified Organisms. WIRN 2013: 241-249 - 2012
- [c11]Antonino Staiano
Investigation of Single Nucleotide Polymorphisms Associated to Familial Combined Hyperlipidemia with Random Forests. WIRN 2012: 169-178 - 2010
- [j8]Giuseppe Calcagno, Antonino Staiano
A multilayer perceptron neural network-based approach for the identification of responsiveness to interferon therapy in multiple sclerosis patients. Inf. Sci. 180(21): 4153-4163 (2010)
2000 – 2009
- 2008
- [j7]Francesco Napolitano
Clustering and visualization approaches for human cell cycle gene expression data analysis. Int. J. Approx. Reason. 47(1): 70-84 (2008) - [j6]Alfredo Petrosino, Antonino Staiano:
Fuzzy modeling for data cleaning in sensor networks. Int. J. Hybrid Intell. Syst. 5(3): 143-151 (2008) - [c10]Alfredo Petrosino, Antonino Staiano
A Neural Based WSN Mote Trajectory Reconstruction for Mining Periodic Patterns. WIRN 2008: 3-11 - 2007
- [c9]Alfredo Petrosino, Antonino Staiano
A Neuro-fuzzy Approach for Sensor Network Data Cleaning. KES (3) 2007: 140-147 - 2006
- [j5]Roberto Amato
A multi-step approach to time series analysis and gene expression clustering. Bioinform. 22(5): 589-596 (2006) - [j4]Antonino Staiano
Improving RBF networks performance in regression tasks by means of a supervised fuzzy clustering. Neurocomputing 69(13-15): 1570-1581 (2006) - 2005
- [c8]Antonino Staiano, Angelo Ciaramella, Lara De Vinco, Giuseppe Longo, Giancarlo Raiconi, Roberto Tagliaferri, Roberto Amato, Carmine Del Mondo, Giuseppe Mangano, Gennaro Miele:
Visualization, Clustering and Classification of Multidimensional Astronomical Data. CAMP 2005: 141-146 - [c7]Roberto Amato
NEC for Gene Expression Analysis. WILF 2005: 246-251 - [c6]Angelo Ciaramella
NEC: A Hierarchical Agglomerative Clustering Based on Fisher and Negentropy Information. WIRN/NAIS 2005: 49-56 - 2004
- [b1]Antonino Staiano:
Unsupervised neural networks for the extraction of scientific information from astronomical data. University of Salerno, Italy, 2004 - [c5]Antonino Staiano
Probabilistic Principal Surfaces for Yeast Gene Microarray Data Mining. ICDM 2004: 202-208 - [c4]Antonino Staiano, Roberto Tagliaferri, Lara De Vinco, Angelo Ciaramella, Giancarlo Raiconi, Giuseppe Longo, Gennaro Miele, Roberto Amato, Carmine Del Mondo, Ciro Donalek, Giuseppe Mangano, Diego di Bernardo:
Mining Yeast Gene Microarray Data with Latent Variable Models. WIRN 2004: 81-89 - 2003
- [j3]Roberto Tagliaferri
Neural neZtworks in astronomy. Neural Networks 16(3-4): 297-319 (2003) - [c3]Antonino Staiano, Roberto Tagliaferri, Witold Pedrycz:
Linear Regression Model-Guided Clustering for Training RBF Networks for Regression Problems. WILF 2003: 127-132 - 2002
- [j2]Antonio Di Nola, Vincenzo Loia, Antonino Staiano
An Evolutionary Approach to Spatial Fuzzy c-Means Clustering. Fuzzy Optim. Decis. Mak. 1(2): 195-219 (2002) - 2000
- [j1]Vincenzo Loia, Salvatore Sessa, Antonino Staiano, Roberto Tagliaferri:
Merging fuzzy logic, neural networks, and genetic computation in the design of a decision-support system. Int. J. Intell. Syst. 15(7): 575-594 (2000) - [c2]Antonio Di Nola, Vincenzo Loia, Antonino Staiano:
Genetic-based spatial clustering. FUZZ-IEEE 2000: 953-956 - [c1]Vincenzo Loia, Antonino Staiano
An Evolutionary Hybrid Approach to the Design of a Decision Support System. SAC (1) 2000: 524-528
Coauthor Index
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last updated on 2024-11-07 20:33 CET by the dblp team
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