Sfoglia per Titolo
Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model
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A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems
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Machine Learning for Utility Prediction in Argument-Based Computational Persuasion
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Machine Learning Generalisation across Different 3D Architectural Heritage
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Machine learning methods for predictive proteomics
2008-01-01 A., Barla; Jurman, Giuseppe; Riccadonna, Samantha; Chierici, Marco; Merler, Stefano; Furlanello, Cesare
Machine learning methods to understand hepatocellular carcinoma pathology
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Machine Learning Models Cannot Replace Screening Colonoscopy for the Prediction of Advanced Colorectal Adenoma
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Machine learning models for predicting endocrine disruption potential of environmental chemicals
2019-01-01 Chierici, Marco; Giulini, Marco; Bussola, Nicole; Jurman, Giuseppe; Furlanello, Cesare
Machine learning on historic air photographs for mapping risk of unexploded bombs
2005-01-01 Merler, Stefano; Furlanello, Cesare; Jurman, Giuseppe
Machine learning on historic air photographs for mapping risk of unexploded bombs
2003-01-01 Merler, Stefano; Furlanello, Cesare
A machine learning pipeline for quantitative phenotype prediction from genotype data
2010-01-01 Guzzetta, Giorgio; Jurman, Giuseppe; Furlanello, Cesare
Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation
2021-01-01 Mamandipoor, Behrooz; Frutos-Vivar, Fernando; Peñuelas, Oscar; Rezar, Richard; Raymondos, Konstantinos; Muriel, Alfonso; Du, Bin; Thille, Arnaud W; Ríos, Fernando; González, Marco; Del-Sorbo, Lorenzo; Del Carmen Marín, Maria; Pinheiro, Bruno Valle; Soares, Marco Antonio; Nin, Nicolas; Maggiore, Salvatore M; Bersten, Andrew; Kelm, Malte; Bruno, Raphael Romano; Amin, Pravin; Cakar, Nahit; Suh, Gee Young; Abroug, Fekri; Jibaja, Manuel; Matamis, Dimitros; Zeggwagh, Amine Ali; Sutherasan, Yuda; Anzueto, Antonio; Wernly, Bernhard; Esteban, Andrés; Jung, Christian; Osmani, Venet
Machine learning predicts mortality in septic patients using only routinely available ABG variables: a multi-centre evaluation
2021-01-01 Wernly, Bernhard; Mamandipoor, Behrooz; Baldia, Philipp; Jung, Christian; Osmani, Venet
Machine Learning-Based Dynamic Attribute Selection Technique for DDoS Attack Classification in IoT Networks
2023-01-01 Ullah, Subhan; Mahmood, Zahid; Ali, Nabeel; Ahmad, Tahir; Buriro, Attaullah
Machine learning-driven Scaling and Placement of Virtual Network Functions at the Network Edges
2019-01-01 Subramanya, Tejas; Riggio, Roberto
Titolo | Data di pubblicazione | Autore(i) | File |
---|---|---|---|
Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model | 1-gen-2023 | Borré, Andressa; Seman, Laio Oriel; Camponogara, Eduardo; Stefenon, Stefano Frizzo; Mariani, Viviana Cocco; Coelho, Leandro dos Santos | |
Machine Learning and Data Analytics in Pervasive Health | 1-gen-2018 | Oliver, N; Mayora, O; Marschollek, M | |
Machine Learning Applications in the Study of Parkinson’s Disease: A Systematic Review | 1-gen-2023 | Martorell Marugán, Jordi; Chierici, Marco; Bandres-Ciga, Sara; Jurman, Giuseppe; Carmona-Sáez, Pedro | |
A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems | 1-gen-2017 | Montagna, Fabio; Buiatti, Marco; Benatti, Simone; Rossi, Davide; Farella, Elisabetta; Benini, Luca | |
Machine Learning at the Mobile Edge: The Case of Dynamic Adaptive Streaming over HTTP (DASH) | 1-gen-2022 | Behravesh, Rasoul; Rao, Akhila; Perez-Ramirez, Daniel F.; Harutyunyan, Davit; Riggio, Roberto; Boman, Magnus | |
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone | 1-gen-2020 | Chicco, Davide; Jurman, Giuseppe | |
Machine Learning for Personalized Challenges in a Gamified Sustainable Mobility Scenario | 1-gen-2017 | Khoshkangini, Reza; Marconi, Annapaola; Valetto, Giuseppe | |
Machine Learning for Utility Prediction in Argument-Based Computational Persuasion | 1-gen-2022 | Donadello, Ivan; Hunter, Anthony; Teso, Stefano; Dragoni, Mauro | |
Machine Learning Generalisation across Different 3D Architectural Heritage | 1-gen-2020 | Grilli, Eleonora; Remondino, Fabio | |
Machine learning methods for predictive proteomics | 1-gen-2008 | A., Barla; Jurman, Giuseppe; Riccadonna, Samantha; Chierici, Marco; Merler, Stefano; Furlanello, Cesare | |
Machine learning methods to understand hepatocellular carcinoma pathology | 1-gen-2003 | Ciocchetta, Federica; Demichelis, Francesca; Sboner, Andrea | |
Machine Learning Models Cannot Replace Screening Colonoscopy for the Prediction of Advanced Colorectal Adenoma | 1-gen-2021 | Semmler, Georg; Wernly, Sarah; Wernly, Bernhard; Mamandipoor, Behrooz; Bachmayer, Sebastian; Semmler, Lorenz; Aigner, Elmar; Datz, Christian; Osmani, Venet | |
Machine learning models for predicting endocrine disruption potential of environmental chemicals | 1-gen-2019 | Chierici, Marco; Giulini, Marco; Bussola, Nicole; Jurman, Giuseppe; Furlanello, Cesare | |
Machine learning on historic air photographs for mapping risk of unexploded bombs | 1-gen-2005 | Merler, Stefano; Furlanello, Cesare; Jurman, Giuseppe | |
Machine learning on historic air photographs for mapping risk of unexploded bombs | 1-gen-2003 | Merler, Stefano; Furlanello, Cesare | |
A machine learning pipeline for quantitative phenotype prediction from genotype data | 1-gen-2010 | Guzzetta, Giorgio; Jurman, Giuseppe; Furlanello, Cesare | |
Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation | 1-gen-2021 | Mamandipoor, Behrooz; Frutos-Vivar, Fernando; Peñuelas, Oscar; Rezar, Richard; Raymondos, Konstantinos; Muriel, Alfonso; Du, Bin; Thille, Arnaud W; Ríos, Fernando; González, Marco; Del-Sorbo, Lorenzo; Del Carmen Marín, Maria; Pinheiro, Bruno Valle; Soares, Marco Antonio; Nin, Nicolas; Maggiore, Salvatore M; Bersten, Andrew; Kelm, Malte; Bruno, Raphael Romano; Amin, Pravin; Cakar, Nahit; Suh, Gee Young; Abroug, Fekri; Jibaja, Manuel; Matamis, Dimitros; Zeggwagh, Amine Ali; Sutherasan, Yuda; Anzueto, Antonio; Wernly, Bernhard; Esteban, Andrés; Jung, Christian; Osmani, Venet | |
Machine learning predicts mortality in septic patients using only routinely available ABG variables: a multi-centre evaluation | 1-gen-2021 | Wernly, Bernhard; Mamandipoor, Behrooz; Baldia, Philipp; Jung, Christian; Osmani, Venet | |
Machine Learning-Based Dynamic Attribute Selection Technique for DDoS Attack Classification in IoT Networks | 1-gen-2023 | Ullah, Subhan; Mahmood, Zahid; Ali, Nabeel; Ahmad, Tahir; Buriro, Attaullah | |
Machine learning-driven Scaling and Placement of Virtual Network Functions at the Network Edges | 1-gen-2019 | Subramanya, Tejas; Riggio, Roberto |
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