16 citations · 47 across the 7 of their papers we have counts for
8 papers · 1 filter
Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual features matching
Francesco Manigrasso, Lia Morra, Fabrizio Lamberti
Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular, Logic T…
Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification
Luca Piano, Filippo Gabriele Pratticò, Alessandro Sebastian Russo +3
Instance-level object re-identification is a fundamental computer vision task, with applications from image retrieval to intelligent monitoring and fraud detection. In this work, w…
Faster-LTN: a neuro-symbolic, end-to-end object detection architecture
Francesco Manigrasso, Filomeno Davide Miro, Lia Morra +1
The detection of semantic relationships between objects represented in an image is one of the fundamental challenges in image interpretation. Neural-Symbolic techniques, such as Lo…
Breast Mass Detection with Faster R-CNN: On the Feasibility of Learning from Noisy Annotations
Sina Famouri, Lia Morra, Leonardo Mangia +1
In this work we study the impact of noise on the training of object detection networks for the medical domain, and how it can be mitigated by improving the training procedure. Anno…
Object Tracking through Residual and Dense LSTMs
Fabio Garcea, Alessandro Cucco, Lia Morra +1
Visual object tracking task is constantly gaining importance in several fields of application as traffic monitoring, robotics, and surveillance, to name a few. Dealing with changes…
Bridging the gap between Natural and Medical Images through Deep Colorization
Lia Morra, Luca Piano, Fabrizio Lamberti +1
Deep learning has thrived by training on large-scale datasets. However, in many applications, as for medical image diagnosis, getting massive amount of data is still prohibitive du…