PAPETTI, DANIELE MARIA

PAPETTI, DANIELE MARIA  

DIPARTIMENTO DI INFORMATICA, SISTEMISTICA E COMUNICAZIONE  

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Titolo Tipologia Data di pubblicazione Autori File
Machine learning streamlines the morphometric characterization and multi-class segmentation of nuclei in different follicular thyroid lesions: everything in a NUTSHELL 01 - Articolo su rivista 2024 L'Imperio, VincenzoCoelho, VascoCazzaniga, GiorgioPapetti, Daniele MDel Carro, FabioCapitoli, GiuliaMarino, MarioCeku, JorandaIvanova, MariiaGianatti, AndreaNobile, Marco SGalimberti, StefaniaBesozzi, DanielaPagni, Fabio +
Meta-problems in global optimization: new perspectives from Computational Intelligence 07 - Tesi di dottorato Bicocca post 2009 2024 PAPETTI, DANIELE MARIA
An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar 01 - Articolo su rivista 2023 Papetti, Daniele MMenè, RobertoHeilbron, FrancescaPerelli, Francesco PParati, GianfrancoBadano, LuigiBesozzi, DanielaTorlasco, Camilla +
Barcode demultiplexing of nanopore sequencing raw signals by unsupervised machine learning 01 - Articolo su rivista 2023 Papetti, Daniele M.Spolaor, SimoneBesozzi, Daniela +
Estimation of Fuzzy Models from Mixed Data Sets with pyFUME 02 - Intervento a convegno 2023 Papetti, Daniele M.Coelho, VascoNobile, Marco S. +
Evolving Dilation Functions for Parameter Estimation 02 - Intervento a convegno 2023 Papetti, DMCoelho, V
Large T cell clones expressing immune checkpoints increase during multiple myeloma evolution and predict treatment resistance 01 - Articolo su rivista 2023 Papetti, Daniele MNobile, Marco SBesozzi, Daniela +
Method for Determining an Optimal Inversion Time for an "Inversion Recovery" Radio Frequency Pulse Sequence of a Magnetic Resonance for Acquiring Late Images After Administering a Paramagnetic Contrast Medium 06 - Brevetti 2023 Papetti DMTorlasco CNobile MSBesozzi D
Simplifying Fitness Landscapes Using Dilation Functions Evolved With Genetic Programming 01 - Articolo su rivista 2023 Papetti, DMTangherloni, AVanneschi, L +
The Domination Game: Dilating Bubbles to Fill Up Pareto Fronts 02 - Intervento a convegno 2023 Coelho, VPapetti, DTangherloni, ACazzaniga, PBesozzi, DNobile, M
Use of artificial intelligence to automatically predict the optimal patient-specific inversion time for late gadolinium enhancement imaging. Tool development and clinical validation 02 - Intervento a convegno 2023 Papetti, D MMuscogiuri, GBadano, L PParati, GBesozzi, D +
Local Bubble Dilation Functions: Hypersphere-bounded Landscape Deformations Simplify Global Optimization 02 - Intervento a convegno 2022 Papetti, DCoelho, VSpolaor, SBesozzi, D +
Metodo per determinare un tempo di inversione ottimale per una sequenza “Inversion Recovery” di risonanza magnetica utilizzabile per l’acquisizione di immagini tardive dopo somministrazione di un mezzo di contrasto paramagnetico 06 - Brevetti 2022 Besozzi, DPapetti, DTorlasco, CNobile, M
Shaping and Dilating the Fitness Landscape for Parameter Estimation in Stochastic Biochemical Models 01 - Articolo su rivista 2022 Nobile M. S.Papetti D. M.Spolaor S.Manzoni L. +
A comparison of multi-objective optimization algorithms to identify drug target combinations 02 - Intervento a convegno 2021 Spolaor S.Papetti D. M.Besozzi D.Nobile M. S. +
Dark blood ischemic LGE segmentation using a deep learning approach 02 - Intervento a convegno 2021 Torlasco, CPapetti, DBadano, LPParati, GNobile, M +
If You Can't Beat It, Squash It: Simplify Global Optimization by Evolving Dilation Functions 02 - Intervento a convegno 2021 Papetti, DMCazzaniga, PBesozzi, DNobile, MS +
On the automatic calibration of fully analogical spiking neuromorphic chips 02 - Intervento a convegno 2020 Papetti, DMSpolaor, SBesozzi, DAntoniotti, M +
Surfing on Fitness Landscapes: A Boost on Optimization by Fourier Surrogate Modeling 01 - Articolo su rivista 2020 Manzoni, LucaPapetti, Daniele M.Cazzaniga, PaoloSpolaor, SimoneMauri, GiancarloBesozzi, DanielaNobile, Marco S.
Which random is the best random? A study on sampling methods in Fourier surrogate modeling 02 - Intervento a convegno 2020 Nobile, MSSpolaor, SCazzaniga, PPapetti, DMBesozzi, DManzoni, L +