Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Siniosoglou, Ilias"'
Autor:
Siniosoglou, Ilias, Argyriou, Vasileios, Fragulis, George, Fouliras, Panagiotis, Papadopoulos, Georgios Th., Lytos, Anastasios, Sarigiannidis, Panagiotis
The time-consuming nature of training and deploying complicated Machine and Deep Learning (DL) models for a variety of applications continues to pose significant challenges in the field of Machine Learning (ML). These challenges are particularly pron
Externí odkaz:
http://arxiv.org/abs/2409.06904
Autor:
Li, Vladislav, Tsoumplekas, Georgios, Siniosoglou, Ilias, Argyriou, Vasileios, Lytos, Anastasios, Fountoukidis, Eleftherios, Sarigiannidis, Panagiotis
Current methods for low- and few-shot object detection have primarily focused on enhancing model performance for detecting objects. One common approach to achieve this is by combining model finetuning with data augmentation strategies. However, littl
Externí odkaz:
http://arxiv.org/abs/2408.10940
Autor:
Kokkinos, Kyriazis, Polymenidis, Ioannis, Siniosoglou, Ilias, Liatifis, Athanasios, Sarigiannidis, Panagiotis
Data exchange through mobile devices is rapidly increasing due to the high information demands of today's applications. The need for monitoring the exchanged traffic becomes important in order to control and optimize the device and network performanc
Externí odkaz:
http://arxiv.org/abs/2406.18251
Autor:
Tsoumplekas, Georgios, Siniosoglou, Ilias, Argyriou, Vasileios, Moscholios, Ioannis D., Sarigiannidis, Panagiotis
The increased availability of medical data has significantly impacted healthcare by enabling the application of machine / deep learning approaches in various instances. However, medical datasets are usually small and scattered across multiple provide
Externí odkaz:
http://arxiv.org/abs/2405.20430
Autor:
Asimopoulos, Dimitris, Siniosoglou, Ilias, Argyriou, Vasileios, Goudos, Sotirios K., Psannis, Konstantinos E., Karditsioti, Nikoleta, Saoulidis, Theocharis, Sarigiannidis, Panagiotis
In the digital era, with escalating privacy concerns, it's imperative to devise robust strategies that protect private data while maintaining the intrinsic value of textual information. This research embarks on a comprehensive examination of text ano
Externí odkaz:
http://arxiv.org/abs/2405.06709
Autor:
Asimopoulos, Dimitris, Siniosoglou, Ilias, Argyriou, Vasileios, Karamitsou, Thomai, Fountoukidis, Eleftherios, Goudos, Sotirios K., Moscholios, Ioannis D., Psannis, Konstantinos E., Sarigiannidis, Panagiotis
In the realm of data privacy, the ability to effectively anonymise text is paramount. With the proliferation of deep learning and, in particular, transformer architectures, there is a burgeoning interest in leveraging these advanced models for text a
Externí odkaz:
http://arxiv.org/abs/2404.14465
Autor:
Tsoumplekas, Georgios, Li, Vladislav, Siniosoglou, Ilias, Argyriou, Vasileios, Goudos, Sotirios K., Moscholios, Ioannis D., Radoglou-Grammatikis, Panagiotis, Sarigiannidis, Panagiotis
In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and complexity. However, sustainability and energy efficiency have been critic
Externí odkaz:
http://arxiv.org/abs/2403.06631
Akademický článek
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Akademický článek
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K zobrazení výsledku je třeba se přihlásit.
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Autor:
Siniosoglou, Ilias, Argyriou, Vasileios, Lagkas, Thomas, Tsiakalos, Apostolos, Sarigiannidis, Antonios, Sarigiannidis, Panagiotis
Publikováno v:
2021 IEEE Globecom Workshops (GC Wkshps)
Since the introduction of automation technologies in the Industrial field and its subsequent scaling to horizontal and vertical extents, the need for interconnected industrial systems, supporting smart interoperability is ever higher. Due to this sca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e0e1ad5a8af08320f341a01e87a476b
