Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Apostolos Maniatis"'
Publikováno v:
Telecom, Vol 5, Iss 1, Pp 1-20 (2023)
Safety management is a priority to guarantee human-centered manufacturing processes in the context of Industry 5.0, which aims to realize a safe human–machine environment based on knowledge-driven approaches. The traditional approaches for safety m
Externí odkaz:
https://doaj.org/article/6ede413b0d834cf4a0e973e74e439728
Autor:
Konstantinos Psychogyios, Andreas Papadakis, Stavroula Bourou, Nikolaos Nikolaou, Apostolos Maniatis, Theodore Zahariadis
Publikováno v:
Future Internet, Vol 16, Iss 3, p 73 (2024)
The advent of computer networks and the internet has drastically altered the means by which we share information and interact with each other. However, this technological advancement has also created opportunities for malevolent behavior, with indivi
Externí odkaz:
https://doaj.org/article/727f3a6b49d24d8dacf137a0aff7e205
Publikováno v:
Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications.
In recent years, Artificial Intelligence (AI) technology has seen significant growth due to advancements in machine learning (ML) and data processing, as well as the availability of large amounts of data. The integration of AI with eXtended Reality (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8423ee01f64c236f7b3d92d639d658e0
https://doi.org/10.54941/ahfe1002938
https://doi.org/10.54941/ahfe1002938
Publikováno v:
Advances in experimental medicine and biology. 1194
In this paper we present an approach toward human action detection for activities of daily living (ADLs) that uses a convolutional neural network (CNN). The network is trained on discrete Fourier transform (DFT) images that result from raw sensor rea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::f07abfaf823413e0cb3cde03b843090b
https://pubmed.ncbi.nlm.nih.gov/32468527
https://pubmed.ncbi.nlm.nih.gov/32468527
Publikováno v:
Advances in Experimental Medicine and Biology ISBN: 9783030326210
In this paper we present an approach toward human action detection for activities of daily living (ADLs) that uses a convolutional neural network (CNN). The network is trained on discrete Fourier transform (DFT) images that result from raw sensor rea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9dcbae1d885d6e19d93e720e6cbcb359
https://doi.org/10.1007/978-3-030-32622-7_9
https://doi.org/10.1007/978-3-030-32622-7_9
Autor:
Apostolos Maniatis, Antonios Papadakis, Eirini Mathe, Evaggelos Spyrou, Phivos Mylonas, Ioannis Vernikos
Publikováno v:
Engineering Applications of Neural Networks ISBN: 9783030202569
EANN
EANN
In this paper we present an approach for the recognition of human actions targeting at activities of daily living (ADLs). Skeletal information is used to create images capturing the motion of joints in the 3D space. These images are then transformed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5bdbbc1410d22a20468ae526de74f57c
https://doi.org/10.1007/978-3-030-20257-6_44
https://doi.org/10.1007/978-3-030-20257-6_44
Increased pulmonary vascular resistance in pulmonary hypertension (PH) is caused by vasoconstriction and obstruction of small pulmonary arteries by proliferating vascular cells. In analogy to cancer, subsets of proliferating cells may be derived from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2127::3f081e9de5ba436deba42417a1058ed8
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3170768
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3170768
Background: Mortality from severe acute respiratory distress syndrome exceeds 40% and there is no available pharmacologic treatment. Mechanical ventilation contributes to lung dysfunction and mortality by causing ventilator-induced lung injury. We ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2127::62ffb0ef1fc2080e26d2867d32e28100
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3164968
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3164968