Zobrazeno 1 - 10
of 7 639
pro vyhledávání: '"Górka A"'
It is imperative to develop an intrusion prevention system (IPS), specifically designed for autonomous robotic systems. This is due to the unique nature of these cyber-physical systems (CPS), which are not merely typical distributed systems. These sy
Externí odkaz:
http://arxiv.org/abs/2412.19272
An increasing number of individuals, companies and organizations are interested in computing and minimizing the carbon emissions associated with their real-time electricity consumption. To achieve this, they require a carbon signal, i.e. a metric tha
Externí odkaz:
http://arxiv.org/abs/2411.06560
While security vulnerabilities in traditional Deep Neural Networks (DNNs) have been extensively studied, the susceptibility of Spiking Neural Networks (SNNs) to adversarial attacks remains mostly underexplored. Until now, the mechanisms to inject bac
Externí odkaz:
http://arxiv.org/abs/2411.03022
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 1, pp. 190-199, Jan. 2022
A major challenges of deep learning (DL) is the necessity to collect huge amounts of training data. Often, the lack of a sufficiently large dataset discourages the use of DL in certain applications. Typically, acquiring the required amounts of data c
Externí odkaz:
http://arxiv.org/abs/2410.22748
Vehicles are sophisticated machines equipped with sensors that provide real-time data for onboard driving assistance systems. Due to the wide variety of traffic, road, and weather conditions, continuous system enhancements are essential. Connectivity
Externí odkaz:
http://arxiv.org/abs/2410.21934
In this article, we characterize both Lusin's theorem and the existence of Borel representatives via the regularity properties of the measure in general topological measure spaces. As a corollary, we prove that Borel regularity of the measure is both
Externí odkaz:
http://arxiv.org/abs/2410.21434
Artificial Neural Networks (ANNs), commonly mimicking neurons with non-linear functions to output floating-point numbers, consistently receive the same signals of a data point during its forward time. Unlike ANNs, Spiking Neural Networks (SNNs) get v
Externí odkaz:
http://arxiv.org/abs/2409.19413
Autor:
Osorio-Marulanda, Pablo A., Ramirez, John Esteban Castro, Jiménez, Mikel Hernández, Reyes, Nicolas Moreno, Unanue, Gorka Epelde
Creation of synthetic data models has represented a significant advancement across diverse scientific fields, but this technology also brings important privacy considerations for users. This work focuses on enhancing a non-parametric copula-based syn
Externí odkaz:
http://arxiv.org/abs/2409.18611
Despite the impressive performance of autoregressive Language Models (LM) it has been shown that due to reporting bias, LMs lack visual knowledge, i.e. they do not know much about the visual world and its properties. To augment LMs with visual knowle
Externí odkaz:
http://arxiv.org/abs/2409.11148
Due to the high cost of training, large model (LM) practitioners commonly use pretrained models downloaded from untrusted sources, which could lead to owning compromised models. In-context learning is the ability of LMs to perform multiple tasks depe
Externí odkaz:
http://arxiv.org/abs/2409.04142