24 citations · 31 across the 3 of their papers we have counts for
5 papers
The five Is: Key principles for interpretable and safe conversational AI
Mattias Wahde, Marco Virgolin
In this position paper, we present five key principles, namely interpretability, inherent capability to explain, independent data, interactive learning, and inquisitiveness, for th…
Model Learning with Personalized Interpretability Estimation (ML-PIE)
Marco Virgolin, Andrea De Lorenzo, Francesca Randone +2
High-stakes applications require AI-generated models to be interpretable. Current algorithms for the synthesis of potentially interpretable models rely on objectives or regularizat…
Lidar-Camera Co-Training for Semi-Supervised Road Detection
Luca Caltagirone, Lennart Svensson, Mattias Wahde +1
Recent advances in the field of machine learning and computer vision have enabled the development of fast and accurate road detectors. Commonly such systems are trained within a su…
LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks
Luca Caltagirone, Mauro Bellone, Lennart Svensson +1
In this work, a deep learning approach has been developed to carry out road detection by fusing LIDAR point clouds and camera images. An unstructured and sparse point cloud is firs…
Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks
Luca Caltagirone, Samuel Scheidegger, Lennart Svensson +1
In this work, a deep learning approach has been developed to carry out road detection using only LIDAR data. Starting from an unstructured point cloud, top-view images encoding sev…