activity
20182021
most citedDarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments

190 citations · 289 across the 9 of their papers we have counts for

collaborators

22 papers

eess.AS20211 cited

An embedded multichannel sound acquisition system for drone audition

Michael Clayton, Lin Wang, Andrew McPherson +1

Microphone array techniques can improve the acoustic sensing performance on drones, compared to the use of a single microphone. However, multichannel sound acquisition systems are…

cs.CV202011 cited

Underwater image filtering: methods, datasets and evaluation

Chau Yi Li, Riccardo Mazzon, Andrea Cavallaro

Underwater images are degraded by the selective attenuation of light that distorts colours and reduces contrast. The degradation extent depends on the water type, the distance betw…

cs.RO20203 cited

Probabilistic Radio-Visual Active Sensing for Search and Tracking

L. Varotto, A. Cenedese, A. Cavallaro

Active Search and Tracking for search and rescue missions or collaborative mobile robotics relies on the actuation of a sensing platform to detect and localize a target. In this pa…

cs.SD20201 cited

FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances

Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad +3

Speaker identification models are vulnerable to carefully designed adversarial perturbations of their input signals that induce misclassification. In this work, we propose a white-…

cs.LG2020

Robust Latent Representations via Cross-Modal Translation and Alignment

Vandana Rajan, Alessio Brutti, Andrea Cavallaro

Multi-modal learning relates information across observation modalities of the same physical phenomenon to leverage complementary information. Most multi-modal machine learning meth…

cs.CV202025 cited

Exploiting vulnerabilities of deep neural networks for privacy protection

Ricardo Sanchez-Matilla, Chau Yi Li, Ali Shahin Shamsabadi +2

Adversarial perturbations can be added to images to protect their content from unwanted inferences. These perturbations may, however, be ineffective against classifiers that were n…