Zobrazeno 1 - 10
of 1 140
pro vyhledávání: '"Gasteratos, A."'
Autor:
Oikonomou, Katerina Maria, Balaska, Vasiliki, Tsintotas, Konstantinos A., Mavridis, Christos N., Kansizoglou, Ioannis, Gasteratos, Antonios
Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind in achieving the exceptional perfo
Externí odkaz:
http://arxiv.org/abs/2411.14147
Autor:
Gasteratos, Antonios, Tsintotas, Konstantinos A., Fischer, Tobias, Aloimonos, Yiannis, Milford, Michael
Visual-based recognition, e.g., image classification, object detection, etc., is a long-standing challenge in computer vision and robotics communities. Concerning the roboticists, since the knowledge of the environment is a prerequisite for complex n
Externí odkaz:
http://arxiv.org/abs/2411.11481
Autor:
Gasteratos, Ioannis, Jacquier, Antoine
We study concentration properties for laws of non-linear Gaussian functionals on metric spaces. Our focus lies on measures with non-Gaussian tail behaviour which are beyond the reach of Talagrand's classical Transportation-Cost Inequalities (TCIs). M
Externí odkaz:
http://arxiv.org/abs/2310.05750
Autor:
Sevetlidis, Vasileios, Pavlidis, George, Balaska, Vasiliki, Psomoulis, Athanasios, Mouroutsos, Spyridon, Gasteratos, Antonios
In many real-world scenarios, obtaining large amounts of labeled data can be a daunting task. Weakly supervised learning techniques have gained significant attention in recent years as an alternative to traditional supervised learning, as they enable
Externí odkaz:
http://arxiv.org/abs/2303.15092
This study proposes a novel approach for solving the PU learning problem based on an anomaly-detection strategy. Latent encodings extracted from positive-labeled data are linearly combined to acquire new samples. These new samples are used as embeddi
Externí odkaz:
http://arxiv.org/abs/2303.11848
Landing safety is a challenge heavily engaging the research community recently, due to the increasing interest in applications availed by aerial vehicles. In this paper, we propose a landing safety pipeline based on state of the art object detectors
Externí odkaz:
http://arxiv.org/abs/2302.14445
Autor:
Gailus, Siragan, Gasteratos, Ioannis
We consider a multiscale system of stochastic differential equations in which the slow component is perturbed by a small fractional Brownian motion with Hurst index $H>1/2$ and the fast component is driven by an independent Brownian motion. Working i
Externí odkaz:
http://arxiv.org/abs/2210.03678
We develop a provably efficient importance sampling scheme that estimates exit probabilities of solutions to small-noise stochastic reaction-diffusion equations from scaled neighborhoods of a stable equilibrium. The moderate deviation scaling allows
Externí odkaz:
http://arxiv.org/abs/2206.00646
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 11, pp. 19929-19953, Nov. 2022
Where am I? This is one of the most critical questions that any intelligent system should answer to decide whether it navigates to a previously visited area. This problem has long been acknowledged for its challenging nature in simultaneous localizat
Externí odkaz:
http://arxiv.org/abs/2204.12831
Publikováno v:
IEEE Access, Vol 12, Pp 90287-90298 (2024)
In this study, a novel approach for solving the PU learning problem is proposed based on an anomaly detection strategy. A Convolutional Autoencoder (CAE) is used to extract latent encodings from positive-labeled data, which are then linearly combined
Externí odkaz:
https://doaj.org/article/edfb823878e542858f6f7adafb7314e0
