30 citations · 195 across the 14 of their papers we have counts for
14 papers
Mobile Localization Techniques Oriented to Tangible Web
Osvaldo Gervasi, Martina Fortunelli, Riccardo Magni +2
We implemented a system able to locate people indoor, with the purpose of providing assistive services. Such approach is particularly important for the Art, for providing informati…
An Approach for Improving Automatic Mouth Emotion Recognition
Giulio Biondi, Valentina Franzoni, Osvaldo Gervasi +1
The study proposes and tests a technique for automated emotion recognition through mouth detection via Convolutional Neural Networks (CNN), meant to be applied for supporting peopl…
Sharing Linkable Learning Objects with the use of Metadata and a Taxonomy Assistant for Categorization
Valentina Franzoni, Sergio Tasso, Simonetta Pallottelli +1
In this work, a re-design of the Moodledata module functionalities is presented to share learning objects between e-learning content platforms, e.g., Moodle and G-Lorep, in a linka…
Towards a learning-based performance modeling for accelerating Deep Neural Networks
Damiano Perri, Paolo Sylos Labini, Osvaldo Gervasi +2
Emerging applications such as Deep Learning are often data-driven, thus traditional approaches based on auto-tuners are not performance effective across the wide range of inputs us…
High Performance Computing and Computational Intelligence Applications with MultiChaos Perspective
Damiano Perri, Osvaldo Gervasi, Marco Simonetti +1
The experience of the COVID-19 pandemic, which has accelerated many chaotic processes in modern society, has highlighted in a very serious and urgent way the need to understand com…
An example of use of Variational Methods in Quantum Machine Learning
Marco Simonetti, Damiano Perri, Osvaldo Gervasi
This paper introduces a deep learning system based on a quantum neural network for the binary classification of points of a specific geometric pattern (Two-Moons Classification pro…
IoT to monitor people flow in areas of public interest
Damiano Perri, Marco Simonetti, Alex Bordini +2
The unexpected historical period we are living has abruptly pushed us to loosen any sort of interaction between individuals, gradually forcing us to deal with new ways to allow com…
Skin Cancer Classification using Inception Network and Transfer Learning
Priscilla Benedetti, Damiano Perri, Marco Simonetti +3
Medical data classification is typically a challenging task due to imbalance between classes. In this paper, we propose an approach to classify dermatoscopic images from HAM10000 (…
A new method for binary classification of proteins with Machine Learning
Damiano Perri, Marco Simonetti, Andrea Lombardi +2
In this work we set out to find a method to classify protein structures using a Deep Learning methodology. Our Artificial Intelligence has been trained to recognize complex biomole…
Binary classification of proteins by a Machine Learning approach
Damiano Perri, Marco Simonetti, Andrea Lombardi +2
In this work we present a system based on a Deep Learning approach, by using a Convolutional Neural Network, capable of classifying protein chains of amino acids based on the prote…
An immersive Open Source environment using Godot
Francesca Santucci, Federico Frenguelli, Alessandro De Angelis +3
We present a sample implementation of a Virtual and Augmented Reality immersive environment based on Free and Libre Open Source Hardware and Software and the HTC Vive system, used…
Teaching Math with the help of Virtual Reality
Marco Simonetti, Damiano Perri, Natale Amato +1
In the present work we intend to introduce a system based on VR (Virtual Reality) for examining analytical-geometric structures that occur in the study of mathematics and physics c…
Implementing a scalable and elastic computing environment based on Cloud Containers
Damiano Perri, Marco Simonetti, Sergio Tasso +2
In this article we look at the potential of cloud containers and we provide some guidelines for companies and organisations that are starting to look at how to migrate their legacy…
A model-driven approach for a new generation of adaptive libraries
Marco Cianfriglia, Flavio Vella, Cedric Nugteren +2
Efficient high-performance libraries often expose multiple tunable parameters to provide highly optimized routines. These can range from simple loop unroll factors or vector sizes…