Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Christos Kyrkou"'
Autor:
Christos Kyrkou
Publikováno v:
IET Computer Vision, Vol 14, Iss 7, Pp 417-425 (2020)
Deep‐learning‐based pedestrian detectors can enhance the capabilities of smart camera systems in a wide spectrum of machine vision applications including video surveillance, autonomous driving, robots and drones, smart factory, and health monitor
Externí odkaz:
https://doaj.org/article/a43d1708f8c648b5866cf073f0589494
Autor:
Giuseppe Conti, Christos Kyrkou, Theocharis Theocharides, Gustavo Hernández-Peñaloza, David Jiménez
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2020, Iss 1, Pp 1-16 (2020)
Abstract This paper presents a framework for complete simulation and verification of Serial Digital Interface (SDI) video using a verilog test-bench and geared toward FPGAs. This framework permits simulating the entire process: from test video signal
Externí odkaz:
https://doaj.org/article/6197c064cba547f4ad8d862468d44442
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 1687-1699 (2020)
Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their remote sensing capabilities for many emergency response and disaster mana
Externí odkaz:
https://doaj.org/article/53d625726af34a85aa27cba0c0bf2ec0
Autor:
Giuseppe Conti, Christos Kyrkou, Theocharis Theocharides, Gustavo Hernández-Peñaloza, David Jiménez
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2020, Iss 1, Pp 1-3 (2020)
An amendment to this paper has been published and can be accessed via the original article.
Externí odkaz:
https://doaj.org/article/166f8b92924b49d0b55fb9145a8c996c
Publikováno v:
Proceedings of the IEEE. 111:19-41
Autor:
Antonis Savva, Manos Papageorgiou, Christos Kyrkou, Panayiotis Kolios, Theocharis Theocharides, Christos Panayiotou
Vegetation encroachment in power transmission and distribution networks constitutes a major hazard for the environment and the networks’ integrity, but also for the society at large, with multifaceted consequences. On many occasions the vegetation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::ed03460729ec7683359fe3e95bcba52a
https://zenodo.org/record/8119316
https://zenodo.org/record/8119316
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Autor:
Mohsin Kamal, Christos Kyrkou, Nikos Piperigkos, Andreas Papandreou, Andreas Kloukiniotis, Jordi Casademont, Natlia Porras Mateu, Daniel Baos Castillo, Rodrigo Diaz Rodriguez, Nicola Gregorio Durante, Peter Hofmann, Petros Kapsalas, Aris S. Lalos, Konstantinos Moustakas, Christos Laoudias, Theocharis Theocharides, Georgios Ellinas
Publikováno v:
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::baf29cbfaced1633b2a7ab6175a4ae00
https://hdl.handle.net/2117/374729
https://hdl.handle.net/2117/374729
Autor:
Christos Kyrkou
Publikováno v:
Journal of Real-Time Image Processing
The need for automated real-time visual systems in applications such as smart camera surveillance, smart environments, and drones necessitates the improvement of methods for visual active monitoring and control. Traditionally, the active monitoring t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5e53cb1bb5a7cd77f1fb6566edad4f8
http://arxiv.org/abs/2107.13233
http://arxiv.org/abs/2107.13233
Publikováno v:
ICPR
2020 25th International Conference on Pattern Recognition (ICPR)
2020 25th International Conference on Pattern Recognition (ICPR)
Differentiable architecture search (DARTS) has gained significant attention amongst neural architecture search approaches due to its effectiveness in finding competitive network architectures with affordable computational complexity. However, DARTS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03cacaf159ff0e600f06f5d928f272d6
https://zenodo.org/record/6678111
https://zenodo.org/record/6678111