Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Savvas A. Chatzichristofis"'
Autor:
George Sklias, Socratis Gkelios, Dimitrios Dimitriou, Maria Sartzetaki, Savvas A. Chatzichristofis
Publikováno v:
IEEE Access, Vol 12, Pp 85955-85968 (2024)
In this study, we introduce a versatile and scalable optimization tool designed to address several critical project management needs. Our aim is to provide project managers with a robust decision support system that enhances and streamlines decision-
Externí odkaz:
https://doaj.org/article/c40bb950eed842d69c97038c501844e2
Publikováno v:
IEEE Access, Vol 11, Pp 38208-38217 (2023)
The overall purpose of this study is to propose a novel fine-tuning method for the CLIP architecture that enables the retention of pre-existing knowledge from large datasets and the creation of a domain-agnostic image encoder for universal image embe
Externí odkaz:
https://doaj.org/article/2b880768e8404191b7a6a66b99035513
Autor:
Zinon Zinonos, Socratis Gkelios, Ala F. Khalifeh, Diofantos G. Hadjimitsis, Yiannis S. Boutalis, Savvas A. Chatzichristofis
Publikováno v:
IEEE Access, Vol 10, Pp 122-133 (2022)
Image transmission over Low-Power Wide Area Networks (LP-WAN) protocols has always been a difficult task since it necessitates high data rates and high energy consumption. Long Range (LoRa) is one such protocol, which is excellent for transferring da
Externí odkaz:
https://doaj.org/article/823a9875c3c9474ebab3cc5c886c7b36
Autor:
Savvas D. Apostolidis, Georgios Vougiatzis, Athanasios Ch. Kapoutsis, Savvas A. Chatzichristofis, Elias B. Kosmatopoulos
Publikováno v:
Drones, Vol 7, Iss 6, p 399 (2023)
This work focuses on the efficiency improvement of grid-based Coverage Path Planning (CPP) methodologies in real-world applications with UAVs. While several sophisticated approaches are met in literature, grid-based methods are not commonly used in r
Externí odkaz:
https://doaj.org/article/5574ed0f8eae42d48eb5c1ff85e2697c
Autor:
Salomi Evripidou, Kyriakoula Georgiou, Lefteris Doitsidis, Angelos A. Amanatiadis, Zinon Zinonos, Savvas A. Chatzichristofis
Publikováno v:
IEEE Access, Vol 8, Pp 219534-219562 (2020)
Motivated by the recent explosion of interest around Educational Robotics (ER), this paper attempts to re-approach this area by suggesting new ways of thinking and exploring the related concepts. The contribution of the paper is fourfold. First, futu
Externí odkaz:
https://doaj.org/article/d05ababb78a84dc287bd84c33a8da848
Autor:
Angelos A. Amanatiadis, Savvas A. Chatzichristofis, Konstantinos Charalampous, Lefteris Doitsidis, Elias B. Kosmatopoulos, Phillipos Tsalides, Antonios Gasteratos, Stergios I. Roumeliotis
Publikováno v:
IEEE Access, Vol 1, Pp 691-702 (2013)
Multi-objective robot exploration constitutes one of the most challenging tasks for autonomous robots performing in various operations and different environments. However, the optimal exploration path depends heavily on the objectives and constraints
Externí odkaz:
https://doaj.org/article/7580c02f96584abea4899665d26fe842
Autor:
Kosmatopoulos, Savvas D. Apostolidis, Georgios Vougiatzis, Athanasios Ch. Kapoutsis, Savvas A. Chatzichristofis, Elias B.
Publikováno v:
Drones; Volume 7; Issue 6; Pages: 399
This work focuses on the efficiency improvement of grid-based Coverage Path Planning (CPP) methodologies in real-world applications with UAVs. While several sophisticated approaches are met in literature, grid-based methods are not commonly used in r
Autor:
Georgios Kyprianou, Lefteris Doitsidis, Athanasios Ch. Kapoutsis, Zinon Zinonos, Savvas A. Chatzichristofis
Publikováno v:
2023 IEEE International Conference on Consumer Electronics (ICCE).
Autor:
Savvas A. Chatzichristofis, Nikolaos Bakas, Vagelis Plevris, DIONYSIOS KOUTSANTONIS, Andreas Langousis, Konstantinos Koutsantonis
Publikováno v:
Sustainability; Volume 14; Issue 19; Pages: 12684
In this review paper, we computationally analyze a vast volume of published articles in the field of Adaptive Learning, as obtained by the Scopus Database. Particularly, we use a query with search terms targeting the area of Adaptive Learning Systems