Piastra Marco
Piastra Marco
Потвърден имейл адрес: unipv.it
Online fall detection using recurrent neural networks
M Musci, D De Martini, N Blago, T Facchinetti, M Piastra
arXiv preprint arXiv:1804.04976, 2018
Deep reinforcement learning for collision avoidance of robotic manipulators
B Sangiovanni, A Rendiniello, GP Incremona, A Ferrara, M Piastra
2018 European Control Conference (ECC), 2063-2068, 2018
Embedded real-time fall detection with deep learning on wearable devices
E Torti, A Fontanella, M Musci, N Blago, D Pau, F Leporati, M Piastra
2018 21st euromicro conference on digital system design (DSD), 405-412, 2018
Self-configuring robot path planning with obstacle avoidance via deep reinforcement learning
B Sangiovanni, GP Incremona, M Piastra, A Ferrara
IEEE Control Systems Letters 5 (2), 397-402, 2020
Online fall detection using recurrent neural networks on smart wearable devices
M Musci, D De Martini, N Blago, T Facchinetti, M Piastra
IEEE Transactions on Emerging Topics in Computing 9 (3), 1276-1289, 2020
Embedding recurrent neural networks in wearable systems for real-time fall detection
E Torti, A Fontanella, M Musci, N Blago, D Pau, F Leporati, M Piastra
Microprocessors and Microsystems 71, 102895, 2019
Distributed and persistent evolutionary algorithms: a design pattern
A Bollini, M Piastra
European Conference on Genetic Programming, 173-183, 1999
Dialogue management in conversational agents through psychology of persuasion and machine learning
V Carfora, F Di Massimo, R Rastelli, P Catellani, M Piastra
Multimedia Tools and Applications 79 (47), 35949-35971, 2020
Self-organizing adaptive map: Autonomous learning of curves and surfaces from point samples
M Piastra
Neural Networks 41, 96-112, 2013
Phase polarity in a ferrofluid monolayer of shifted-dipole spheres
M Piastra, EG Virga
Soft Matter 8 (42), 10969-10981, 2012
Deep recurrent neural networks for edge monitoring of personal risk and warning situations
E Torti, M Musci, F Guareschi, F Leporati, M Piastra
Scientific Programming 2019, 2019
Deep reinforcement learning based self-configuring integral sliding mode control scheme for robot manipulators
B Sangiovanni, GP Incremona, A Ferrara, M Piastra
2018 IEEE Conference on Decision and Control (CDC), 5969-5974, 2018
Octupolar approximation for the excluded volume of axially symmetric convex bodies
M Piastra, EG Virga
Physical Review E 88 (3), 032507, 2013
A scalable multi-signal approach for the parallelization of self-organizing neural networks
M Musci, G Parigi, V Cantoni, M Piastra
Neural Networks 123, 108-117, 2020
A 3D packaging technology for acoustically optimized integration of 2D CMUT arrays and front end circuits
AS Savoia, B Mauti, G Caliano, G Matrone, M Piastra, R Bardelli, F Toia, ...
2017 IEEE International Ultrasonics Symposium (IUS), 1-4, 2017
Applying Psychology of Persuasion to Conversational Agents through Reinforcement Learning: an Exploratory Study.
F Di Massimo, V Carfora, P Catellani, M Piastra
CLiC-it, 2019
A multi-signal variant for the gpu-based parallelization of growing self-organizing networks
G Parigi, A Stramieri, D Pau, M Piastra
Informatics in Control, Automation and Robotics, 83-100, 2014
Computing the Reeb Graph for Triangle Meshes with Active Contours.
L Brandolini, M Piastra
ICPRAM (2) 12, 80-89, 2012
A growing self-organizing network for reconstructing curves and surfaces
M Piastra
2009 International Joint Conference on Neural Networks, 2533-2540, 2009
An efficient context-free parsing algorithm with semantic actions
M Piastra, R Bolognesi
Congress of the Italian Association for Artificial Intelligence, 271-280, 1991
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