128 citations · 293 across the 39 of their papers we have counts for
7 papers · 1 filter
Class Distribution Monitoring for Concept Drift Detection
Diego Stucchi, Luca Frittoli, Giacomo Boracchi
We introduce Class Distribution Monitoring (CDM), an effective concept-drift detection scheme that monitors the class-conditional distributions of a datastream. In particular, our…
Composite Convolution: a Flexible Operator for Deep Learning on 3D Point Clouds
Alberto Floris, Luca Frittoli, Diego Carrera +1
Deep neural networks require specific layers to process point clouds, as the scattered and irregular location of 3D points prevents the use of conventional convolutional filters. W…
Nonparametric and Online Change Detection in Multivariate Datastreams using QuantTree
Luca Frittoli, Diego Carrera, Giacomo Boracchi
We address the problem of online change detection in multivariate datastreams, and we introduce QuantTree Exponentially Weighted Moving Average (QT-EWMA), a nonparametric change-de…
Deep Open-Set Recognition for Silicon Wafer Production Monitoring
Luca Frittoli, Diego Carrera, Beatrice Rossi +2
The chips contained in any electronic device are manufactured over circular silicon wafers, which are monitored by inspection machines at different production stages. Inspection ma…
Deep Autoencoders for Anomaly Detection in Textured Images using CW-SSIM
Andrea Bionda, Luca Frittoli, Giacomo Boracchi
Detecting anomalous regions in images is a frequently encountered problem in industrial monitoring. A relevant example is the analysis of tissues and other products that in normal…
Perception Visualization: Seeing Through the Eyes of a DNN
Loris Giulivi, Mark James Carman, Giacomo Boracchi
Artificial intelligence (AI) systems power the world we live in. Deep neural networks (DNNs) are able to solve tasks in an ever-expanding landscape of scenarios, but our eagerness…
Adversarial Scratches: Deployable Attacks to CNN Classifiers
Loris Giulivi, Malhar Jere, Loris Rossi +4
A growing body of work has shown that deep neural networks are susceptible to adversarial examples. These take the form of small perturbations applied to the model's input which le…