no code implementations • 5 Oct 2024 • Dominika Woszczyk, Soteris Demetriou
Dementia is a sensitive neurocognitive disorder affecting tens of millions of people worldwide and its cases are expected to triple by 2050.
1 code implementation • 3 Jul 2024 • Dominika Woszczyk, Ranya Aloufi, Soteris Demetriou
In this work, we aim to anonymize embeddings while preserving the diagnostic utility for dementia detection.
no code implementations • 1 Jun 2024 • Chengzeng You, Zhongyuan Hau, Binbin Xu, Soteris Demetriou
LiDAR sensors are widely used in autonomous vehicles to better perceive the environment.
1 code implementation • 26 Jun 2022 • Anna Hlédiková, Dominika Woszczyk, Alican Akman, Soteris Demetriou, Björn Schuller
In this work, we investigate data augmentation techniques for the task of AD detection and perform an empirical evaluation of the different approaches on two kinds of models for both the text and audio domains.
no code implementations • 29 Apr 2022 • Zhongyuan Hau, Soteris Demetriou, Emil C. Lupu
We achieve this by searching for void regions and locating the obstacles that cause these shadows.
no code implementations • 15 Jun 2021 • Chengzeng You, Zhongyuan Hau, Soteris Demetriou
In particular, model-level LiDAR spoofing attacks aim to inject fake depth measurements to elicit ghost objects that are erroneously detected by 3D Object Detectors, resulting in hazardous driving decisions.
no code implementations • 28 May 2021 • Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Soteris Demetriou, Deniz Gündüz, Hamed Haddadi
Our proposed framework enables clients to localize and quantify the private information leakage in a layer-wise manner, and enables a better understanding of the sources of information leakage in collaborative learning, which can be used by future studies to benchmark new attacks and defense mechanisms.
no code implementations • 7 Feb 2021 • Zhongyuan Hau, Kenneth T. Co, Soteris Demetriou, Emil C. Lupu
LiDARs play a critical role in Autonomous Vehicles' (AVs) perception and their safe operations.
no code implementations • 17 Oct 2020 • Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou
Training deep neural networks via federated learning allows clients to share, instead of the original data, only the model trained on their data.
2 code implementations • 12 Apr 2020 • Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi
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 Neural Networks (DNNs).
no code implementations • 28 Mar 2017 • Nan Zhang, Soteris Demetriou, Xianghang Mi, Wenrui Diao, Kan Yuan, Peiyuan Zong, Feng Qian, Xiao-Feng Wang, Kai Chen, Yuan Tian, Carl A. Gunter, Kehuan Zhang, Patrick Tague, Yue-Hsun Lin
We systemize this process, by proposing a taxonomy for the IoT ecosystem and organizing IoT security into five problem areas.
Cryptography and Security