Zobrazeno 1 - 10
of 2 241
pro vyhledávání: '"MULTIMODAL ANALYSIS"'
Autor:
ALINA MOZOLEVSKA
Publikováno v:
Czech Journal of International Relations, Vol 59, Iss 2, Pp 7-37 (2024)
The article examines the generation and deployment of visual narratives in Ukrainian and Russian digital participatory cultures, with a specific focus on internet memes in the context of the Russian invasion of Ukraine. It analyzes the form, content,
Externí odkaz:
https://doaj.org/article/a054bb2f67cc4cfabe205c1f3e4e7602
Autor:
Wojciech Kułaga
Publikováno v:
Przeglad Socjologii Jakosciowej, Vol 20, Iss 3, Pp 212-235 (2024)
TikTok, a swiftly expanding social media platform, has emerged as a potent catalyst in transforming the realm of visual communication and digital interaction. This paper explores the evolving landscape of TikTok, focusing on its technological advance
Externí odkaz:
https://doaj.org/article/04510d5aa2f74097b3037f4550358e91
Publikováno v:
Frontiers in Neuroergonomics, Vol 5 (2024)
Externí odkaz:
https://doaj.org/article/1c6e069215134a90a2467d5f70a12ff0
Autor:
Jiayuan Ding, Renming Liu, Hongzhi Wen, Wenzhuo Tang, Zhaoheng Li, Julian Venegas, Runze Su, Dylan Molho, Wei Jin, Yixin Wang, Qiaolin Lu, Lingxiao Li, Wangyang Zuo, Yi Chang, Yuying Xie, Jiliang Tang
Publikováno v:
Genome Biology, Vol 25, Iss 1, Pp 1-28 (2024)
Abstract DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules
Externí odkaz:
https://doaj.org/article/82df36dc168a46dcab46d25ab356cce5
Publikováno v:
IEEE Access, Vol 12, Pp 127782-127791 (2024)
Classification models using deep or machine learning algorithms require a sufficient and balanced training dataset to improve performance. Still, they suffer from data collection due to data privacy issues. In medical research, where most data variab
Externí odkaz:
https://doaj.org/article/8479e5104d4b48e9be00d302a6072f27
Autor:
Premnarayan Arya, Amit Kumar Pandey, S. Gopal Krishna Patro, Kretika Tiwari, Niranjan Panigrahi, Quadri Noorulhasan Naveed, Ayodele Lasisi, Wahaj Ahmad Khan
Publikováno v:
IEEE Access, Vol 12, Pp 73700-73718 (2024)
In an era where social media platforms burgeon with diverse content, compelling moderation is imperative to filter harmful materials. Traditional methods often grapple with the dual challenges of accuracy and computational efficiency levels. These co
Externí odkaz:
https://doaj.org/article/989d0d9b35f64df8982ab15011cb14b2
Autor:
Ennio Idrobo-Avila, Gergo Bognar, Dagmar Krefting, Thomas Penzel, Peter Kovacs, Nicolai Spicher
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 250-260 (2024)
Goal: Recently, large datasets of biosignals acquired during surgery became available. As they offer multiple physiological signals measured in parallel, multimodal analysis – which involves their joint analysis – can be conducted and could provi
Externí odkaz:
https://doaj.org/article/96496275904c4bf7a45cf90e2edfeed7
Autor:
Marcos Loaiza-Arias, Andrés Marino Álvarez-Meza, David Cárdenas-Peña, Álvaro Ángel Orozco-Gutierrez, German Castellanos-Dominguez
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 11208 (2024)
Brain–computer interfaces (BCIs) are essential in advancing medical diagnosis and treatment by providing non-invasive tools to assess neurological states. Among these, motor imagery (MI), in which patients mentally simulate motor tasks without phys
Externí odkaz:
https://doaj.org/article/95fe16b456ae45c3b5cbc6e7b98a3d38
Autor:
Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 11075 (2024)
In this article, we propose the detection of crowd anomalies through the extraction of information in the form of time series in video format using a multimodal approach. Through pattern recognition algorithms and segmentation, informative measures o
Externí odkaz:
https://doaj.org/article/4fa55f54245c4d7fbd8504e199562a51
Publikováno v:
Heliyon, Vol 10, Iss 8, Pp e29596- (2024)
Falls often pose significant safety risks to solitary individuals, especially the elderly. Implementing a fast and efficient fall detection system is an effective strategy to address this hidden danger. We propose a multimodal method based on audio a
Externí odkaz:
https://doaj.org/article/833209708b3c47dc98ed941d1d7700ca