128 citations · 293 across the 39 of their papers we have counts for
40 papers
Weakly Supervised Polar Low Segmentation in Sentinel-1 SAR Imagery
Andrea Federici, Jakob Grahn, Giacomo Boracchi +1
Polar lows are intense maritime cyclones that form rapidly at high latitudes. Deep learning can detect them in Synthetic Aperture Radar (SAR) imagery, but pixel-level segmentation…
SAR Vessel Detection and Gross Tonnage Estimation from Heterogeneous Datasets for Dark Vessel Identification
Davide Paltrinieri, Andrea Diecidue, Roberto Basla +3
Detecting vessels engaging in illegal activities is of paramount importance for maritime security. One of the major goals is to detect dark vessels, ships that disable their transp…
Cell Phantom Video Generation in Elliptical Fourier Descriptor Domain
Francesco Benedetto, Roberto Basla, Luca Magri +1
Training Deep Neural Networks for tracking individual cells in biomedical videos requires a large amount of annotated data. The annotation of videos for cell tracking is very time…
Accurate Simulation Pipeline for Passive Single-Photon Imaging
Aleksi Suonsivu, Lauri Salmela, Leevi Uosukainen +3
Single-Photon Avalanche Diodes (SPADs) are new and promising imaging sensors. These sensors are sensitive enough to detect individual photons hitting each pixel, with extreme tempo…
LCF3D: A Robust and Real-Time Late-Cascade Fusion Framework for 3D Object Detection in Autonomous Driving
Carlo Sgaravatti, Riccardo Pieroni, Matteo Corno +3
Accurately localizing 3D objects like pedestrians, cyclists, and other vehicles is essential in Autonomous Driving. To ensure high detection performance, Autonomous Vehicles comple…
Promptable Foundation Models for SAR Remote Sensing: Adapting the Segment Anything Model for Snow Avalanche Segmentation
Riccardo Gelato, Carlo Sgaravatti, Jakob Grahn +2
Remote sensing solutions for avalanche segmentation and mapping are key to supporting risk forecasting and mitigation in mountain regions. Synthetic Aperture Radar (SAR) imagery fr…
One target to align them all: LiDAR, RGB and event cameras extrinsic calibration for Autonomous Driving
Andrea Bertogalli, Giacomo Boracchi, Luca Magri
We present a novel multi-modal extrinsic calibration framework designed to simultaneously estimate the relative poses between event cameras, LiDARs, and RGB cameras, with particula…
Convolutional Set Transformer
Federico Chinello, Giacomo Boracchi
We introduce the Convolutional Set Transformer (CST), a novel neural architecture designed to process image sets of arbitrary cardinality that are visually heterogeneous yet share…
WS: Weakly Supervised Segmentation using Before-After Supervision in Waste Sorting
Andrea Marelli, Alberto Foresti, Leonardo Pesce +2
In industrial quality control, to visually recognize unwanted items within a moving heterogeneous stream, human operators are often still indispensable. Waste-sorting stands as a s…
Biasing Frontier-Based Exploration with Saliency Areas
Matteo Luperto, Valerii Stakanov, Giacomo Boracchi +2
Autonomous exploration is a widely studied problem where a robot incrementally builds a map of a previously unknown environment. The robot selects the next locations to reach using…
Malware families discovery via Open-Set Recognition on Android manifest permissions
Filippo Leveni, Matteo Mistura, Francesco Iubatti +4
Malware are malicious programs that are grouped into families based on their penetration technique, source code, and other characteristics. Classifying malware programs into their…
MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model Selection
Luca Magri, Filippo Leveni, Giacomo Boracchi
We address the problem of recovering multiple structures of different classes in a dataset contaminated by noise and outliers. In particular, we consider geometric structures defin…
Hashing for Structure-based Anomaly Detection
Filippo Leveni, Luca Magri, Cesare Alippi +1
We focus on the problem of identifying samples in a set that do not conform to structured patterns represented by low-dimensional manifolds. An effective way to solve this problem…
PIF: Anomaly detection via preference embedding
Filippo Leveni, Luca Magri, Giacomo Boracchi +1
We address the problem of detecting anomalies with respect to structured patterns. To this end, we conceive a novel anomaly detection method called PIF, that combines the advantage…
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer +2
The anomaly detection literature is abundant with offline methods, which require repeated access to data in memory, and impose impractical assumptions when applied to a streaming c…
Preference Isolation Forest for Structure-based Anomaly Detection
Filippo Leveni, Luca Magri, Cesare Alippi +1
We address the problem of detecting anomalies as samples that do not conform to structured patterns represented by low-dimensional manifolds. To this end, we conceive a general ano…
A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object Detection
Carlo Sgaravatti, Roberto Basla, Riccardo Pieroni +4
We present a new way to detect 3D objects from multimodal inputs, leveraging both LiDAR and RGB cameras in a hybrid late-cascade scheme, that combines an RGB detection network and…
Adaptive Extended Kalman Filtering for Battery State of Charge Estimation on STM32
António Barros, Edoardo Peretti, Davide Fabroni +3
Accurate and computationally light algorithms for estimating the State of Charge (SoC) of a battery's cells are crucial for effective battery management on embedded systems. In thi…
Temporal-consistent CAMs for Weakly Supervised Video Segmentation in Waste Sorting
Andrea Marelli, Luca Magri, Federica Arrigoni +1
In industrial settings, weakly supervised (WS) methods are usually preferred over their fully supervised (FS) counterparts as they do not require costly manual annotations. Unfortu…
A Deep Learning Pipeline for Solid Waste Detection in Remote Sensing Images
Federico Gibellini, Piero Fraternali, Giacomo Boracchi +4
Improper solid waste management represents both a serious threat to ecosystem health and a significant source of revenues for criminal organizations perpetrating environmental crim…
Time-Resolved MNIST Dataset for Single-Photon Recognition
Aleksi Suonsivu, Lauri Salmela, Edoardo Peretti +3
Time-resolved single photon imaging is a promising imaging modality characterized by the unique capability of timestamping the arrivals of single photons. Single-Photon Avalanche D…
Change Detection in Multivariate data streams: Online Analysis with Kernel-QuantTree
Michelangelo Olmo Nogara Notarianni, Filippo Leveni, Diego Stucchi +2
We present Kernel-QuantTree Exponentially Weighted Moving Average (KQT-EWMA), a non-parametric change-detection algorithm that combines the Kernel-QuantTree (KQT) histogram and the…
Deep Learning for identifying systolic complexes in SCG traces: a cross-dataset analysis
Michele Craighero, Sarah Solbiati, Federica Mozzini +2
The seismocardiographic signal is a promising alternative to the traditional ECG in the analysis of the cardiac activity. In particular, the systolic complex is known to be the mos…
AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection
Yunkang Cao, Jiangning Zhang, Luca Frittoli +3
Zero-shot anomaly detection (ZSAD) targets the identification of anomalies within images from arbitrary novel categories. This study introduces AdaCLIP for the ZSAD task, leveragin…