4 citations · 6 across the 5 of their papers we have counts for
6 papers
Adversarial Attack Against Image-Based Localization Neural Networks
Meir Brand, Itay Naeh, Daniel Teitelman
In this paper, we present a proof of concept for adversarially attacking the image-based localization module of an autonomous vehicle. This attack aims to cause the vehicle to perf…
Robustness through Cognitive Dissociation Mitigation in Contrastive Adversarial Training
Adir Rahamim, Itay Naeh
In this paper, we introduce a novel neural network training framework that increases model's adversarial robustness to adversarial attacks while maintaining high clean accuracy by…
Stealing Black-Box Functionality Using The Deep Neural Tree Architecture
Daniel Teitelman, Itay Naeh, Shie Mannor
This paper makes a substantial step towards cloning the functionality of black-box models by introducing a Machine learning (ML) architecture named Deep Neural Trees (DNTs). This n…
Over-the-Air Adversarial Flickering Attacks against Video Recognition Networks
Roi Pony, Itay Naeh, Shie Mannor
Deep neural networks for video classification, just like image classification networks, may be subjected to adversarial manipulation. The main difference between image classifiers…
Interpreting Electrical-Resistivity Tomography measurements using Neural Network
Itay Naeh, Yitzhak Peleg, Alex Furman +1
Electrical Resistivity Tomography (ERT) has been extensively used for imaging the subsurface resistivity distribution and structure. Over the years, many algorithms have been devel…
Handling massive spatial volumes in time domain simulations using Triggered Cells Method
I. Naeh
Simulating wave propagation on discrete grid in time domain requires the description of both the parameters of the media and the values of the wave field at two different time step…