128 citations · 293 across the 39 of their papers we have counts for
9 papers · 1 filter
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…
Estimating Map Completeness in Robot Exploration
Matteo Luperto, Marco Maria Ferrara, Giacomo Boracchi +1
In this paper, we propose a method that, given a partial grid map of an indoor environment built by an autonomous mobile robot, estimates the amount of the explored area represente…
An expert-driven data generation pipeline for histological images
Roberto Basla, Loris Giulivi, Luca Magri +1
Deep Learning (DL) models have been successfully applied to many applications including biomedical cell segmentation and classification in histological images. These models require…
Explaining Multi-modal Large Language Models by Analyzing their Vision Perception
Loris Giulivi, Giacomo Boracchi
Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in understanding and generating content across various modalities, such as images and text. Howe…
Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNet
Loris Giulivi, Giacomo Boracchi
Advances in multi-modal embeddings, and in particular CLIP, have recently driven several breakthroughs in Computer Vision (CV). CLIP has shown impressive performance on a variety o…
SE3D: A Framework For Saliency Method Evaluation In 3D Imaging
Mariusz Wiśniewski, Loris Giulivi, Giacomo Boracchi
For more than a decade, deep learning models have been dominating in various 2D imaging tasks. Their application is now extending to 3D imaging, with 3D Convolutional Neural Networ…