190 citations · 295 across the 16 of their papers we have counts for
8 papers · 1 filter
Data augmentation with mixtures of max-entropy transformations for filling-level classification
Apostolos Modas, Andrea Cavallaro, Pascal Frossard
We address the problem of distribution shifts in test-time data with a principled data augmentation scheme for the task of content-level classification. In such a task, properties…
Is Cross-Attention Preferable to Self-Attention for Multi-Modal Emotion Recognition?
Vandana Rajan, Alessio Brutti, Andrea Cavallaro
Humans express their emotions via facial expressions, voice intonation and word choices. To infer the nature of the underlying emotion, recognition models may use a single modality…
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…
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas +4
We present DarkneTZ, a framework that uses an edge device's Trusted Execution Environment (TEE) in conjunction with model partitioning to limit the attack surface against Deep Neur…
Privacy and Utility Preserving Sensor-Data Transformations
Mohammad Malekzadeh, Richard G. Clegg, Andrea Cavallaro +1
Sensitive inferences and user re-identification are major threats to privacy when raw sensor data from wearable or portable devices are shared with cloud-assisted applications. To…
EdgeFool: An Adversarial Image Enhancement Filter
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
Adversarial examples are intentionally perturbed images that mislead classifiers. These images can, however, be easily detected using denoising algorithms, when high-frequency spat…