Zobrazeno 1 - 10
of 1 898
pro vyhledávání: '"Tefas, A."'
Autor:
Kirtas, Manos, Tsampazis, Konstantinos, Avramelou, Loukia, Passalis, Nikolaos, Tefas, Anastasios
Utilizing deep learning models to learn part-based representations holds significant potential for interpretable-by-design approaches, as these models incorporate latent causes obtained from feature representations through simple addition. However, t
Externí odkaz:
http://arxiv.org/abs/2408.11455
In this study a model pipeline is proposed that combines computer vision with control-theoretic methods and utilizes low cost sensors. The proposed work enables perception-aware motion control for a quadrotor UAV to detect and navigate to objects of
Externí odkaz:
http://arxiv.org/abs/2407.15122
Autor:
Koloniari, Alexandra E., Koursoumpa, Evdokia C., Nousi, Paraskevi, Lampropoulos, Paraskevas, Passalis, Nikolaos, Tefas, Anastasios, Stergioulas, Nikolaos
The detection of gravitational waves has revolutionized our understanding of the universe, offering unprecedented insights into its dynamics. A major goal of gravitational wave data analysis is to speed up the detection and parameter estimation proce
Externí odkaz:
http://arxiv.org/abs/2407.07820
Deep Learning (DL) has brought significant advances to robotics vision tasks. However, most existing DL methods have a major shortcoming, they rely on a static inference paradigm inherent in traditional computer vision pipelines. On the other hand, r
Externí odkaz:
http://arxiv.org/abs/2312.10200
Autor:
Tsakyridis, A., Moralis-Pegios, M., Giamougiannis, G., Kirtas, M., Passalis, N., Tefas, A., Pleros, N.
The recent explosive compute growth, mainly fueled by the boost of AI and DNNs, is currently instigating the demand for a novel computing paradigm that can overcome the insurmountable barriers imposed by conventional electronic computing architecture
Externí odkaz:
http://arxiv.org/abs/2312.00037
Neuromorphic photonic accelerators are becoming increasingly popular, since they can significantly improve computation speed and energy efficiency, leading to femtojoule per MAC efficiency. However, deploying existing DL models on such platforms is n
Externí odkaz:
http://arxiv.org/abs/2310.01084
Autor:
Nousi, Paraskevi, Avramelou, Loukia, Rodinos, Georgios, Tzelepi, Maria, Manousis, Theodoros, Tsampazis, Konstantinos, Stefanidis, Kyriakos, Spanos, Dimitris, Kirtas, Manos, Tosidis, Pavlos, Tsantekidis, Avraam, Passalis, Nikolaos, Tefas, Anastasios
Financial portfolio management describes the task of distributing funds and conducting trading operations on a set of financial assets, such as stocks, index funds, foreign exchange or cryptocurrencies, aiming to maximize the profit while minimizing
Externí odkaz:
http://arxiv.org/abs/2309.16679
Even nowadays, where Deep Learning (DL) has achieved state-of-the-art performance in a wide range of research domains, accelerating training and building robust DL models remains a challenging task. To this end, generations of researchers have pursue
Externí odkaz:
http://arxiv.org/abs/2307.07189
Autor:
Tzelepi, Maria, Symeonidis, Charalampos, Nousi, Paraskevi, Kakaletsis, Efstratios, Manousis, Theodoros, Tosidis, Pavlos, Nikolaidis, Nikos, Tefas, Anastasios
Energy time-series analysis describes the process of analyzing past energy observations and possibly external factors so as to predict the future. Different tasks are involved in the general field of energy time-series analysis and forecasting, with
Externí odkaz:
http://arxiv.org/abs/2306.09129
Autor:
Oleksiienko, Illia, Nousi, Paraskevi, Passalis, Nikolaos, Tefas, Anastasios, Iosifidis, Alexandros
Uncertainty estimation is an important task for critical problems, such as robotics and autonomous driving, because it allows creating statistically better perception models and signaling the model's certainty in its predictions to the decision metho
Externí odkaz:
http://arxiv.org/abs/2302.05914