Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Papapanagiotou, Vasileios"'
Autor:
Tatli, Dimitra, Papapanagiotou, Vasileios, Liakos, Aris, Tsapas, Apostolos, Delopoulos, Anastasios
Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention and prevention of complications. This research explores the feasibili
Externí odkaz:
http://arxiv.org/abs/2410.02692
Transportation mode recognition (TMR) is a critical component of human activity recognition (HAR) that focuses on understanding and identifying how people move within transportation systems. It is commonly based on leveraging inertial, location, or b
Externí odkaz:
http://arxiv.org/abs/2404.15323
Despite the recent increase in research activity, deep-learning models have not yet been widely accepted in several real-world settings, such as medicine. The shortage of high-quality annotated data often hinders the development of robust and general
Externí odkaz:
http://arxiv.org/abs/2312.00502
Autor:
van den Boer, Janet, van der Lee, Annemiek, Zhou, Lingchuan, Papapanagiotou, Vasileios, Diou, Christos, Delopoulos, Anastasios, Mars, Monica
Publikováno v:
JMIR mHealth and uHealth, Vol 6, Iss 9, p e170 (2018)
BackgroundThe available methods for monitoring food intake—which for a great part rely on self-report—often provide biased and incomplete data. Currently, no good technological solutions are available. Hence, the SPLENDID eating detection sensor
Externí odkaz:
https://doaj.org/article/55733b8668824fb3a76e1ae958cbf8c0
Heart murmurs are abnormal sounds present in heartbeats, caused by turbulent blood flow through the heart. The PhysioNet 2022 challenge targets automatic detection of murmur from audio recordings of the heart and automatic detection of normal vs. abn
Externí odkaz:
http://arxiv.org/abs/2208.14845
Publikováno v:
Proceedings of the 7th International Workshop on Multimedia Proceedings of the 7th International Workshop on Multimedia Assisted Dietary Management (MADiMa '22), October 10, 2022, Lisboa, Portugal
Automatic dietary monitoring has progressed significantly during the last years, offering a variety of solutions, both in terms of sensors and algorithms as well as in terms of what aspect or parameters of eating behavior are measured and monitored.
Externí odkaz:
http://arxiv.org/abs/2208.05735
Publikováno v:
Appetite, 2022, 106096
The progress in artificial intelligence and machine learning algorithms over the past decade has enabled the development of new methods for the objective measurement of eating, including both the measurement of eating episodes as well as the measurem
Externí odkaz:
http://arxiv.org/abs/2206.02784
While automatic tracking and measuring of our physical activity is a well established domain, not only in research but also in commercial products and every-day life-style, automatic measurement of eating behavior is significantly more limited. Despi
Externí odkaz:
http://arxiv.org/abs/2108.00771
The importance of automated and objective monitoring of dietary behavior is becoming increasingly accepted. The advancements in sensor technology along with recent achievements in machine-learning--based signal-processing algorithms have enabled the
Externí odkaz:
http://arxiv.org/abs/2108.00769
Autor:
Papapanagiotou, Vasileios, Diou, Christos, Boer, Janet van den, Mars, Monica, Delopoulos, Anastasios
Food texture is a complex property; various sensory attributes such as perceived crispiness and wetness have been identified as ways to quantify it. Objective and automatic recognition of these attributes has applications in multiple fields, includin
Externí odkaz:
http://arxiv.org/abs/2105.09621