Zobrazeno 1 - 10
of 7 358
pro vyhledávání: '"convolutional networks"'
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2024, Vol. 17, Issue 4, pp. 869-889.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-07-2024-0317
Autor:
Fu, Zhongxiang, Cao, Buqing, Liu, Shanpeng, Peng, Qian, Peng, Zhenlian, Shi, Min, Liu, Shangli
Publikováno v:
International Journal of Web Information Systems, 2024, Vol. 20, Issue 5, pp. 520-536.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJWIS-06-2024-0178
Publikováno v:
IET Image Processing, Vol 18, Iss 13, Pp 4250-4262 (2024)
Abstract Although graph convolutional networks have achieved good performances in skeleton‐graph‐based action recognition, there are still some problems which include the incomplete utilization of skeleton graph features and the lacking of logica
Externí odkaz:
https://doaj.org/article/3d76010cd50e43eda02a8cc357049eec
Publikováno v:
Advances in Sciences and Technology, Vol 18, Iss 6, Pp 159-176 (2024)
Many scientific studies on tennis stroke recognition are based on datasets created for the purpose of research using video or motion capture techniques. The importance of such datasets has been increasing due to the athlete performance evaluation nee
Externí odkaz:
https://doaj.org/article/8114e0a610e14df4923f9c92b5b0aae5
Autor:
Hong-Jun Yoon, Hilda B. Klasky, Andrew E. Blanchard, J. Blair Christian, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Doherty, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss S5, Pp 1-11 (2024)
Abstract Background Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural
Externí odkaz:
https://doaj.org/article/32c87d99cfdd496bb978027e4ff59d12
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 2111-2129 (2024)
In fashion e-commerce, predicting item compatibility using visual features remains a significant challenge. Current recommendation systems often struggle to incorporate high-dimensional visual data into graph-based learning models effectively. This l
Externí odkaz:
https://doaj.org/article/ebbfe94ab6304116a578a54aa9cd6b6a
Publikováno v:
AI, Vol 5, Iss 3, Pp 1695-1708 (2024)
Human action recognition (HAR) based on skeleton data is a challenging yet crucial task due to its wide-ranging applications, including patient monitoring, security surveillance, and human- machine interaction. Although numerous algorithms have been
Externí odkaz:
https://doaj.org/article/6db5e7cb49744e039fc486429393c144
Publikováno v:
International Journal of Web Information Systems, 2024, Vol. 20, Issue 4, pp. 436-451.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJWIS-03-2024-0087
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 6, Pp 8383-8401 (2024)
Abstract The influence maximization problem that has drawn a great deal of attention from researchers aims to identify a subset of influential spreaders that can maximize the expected influence spread in social networks. Existing works on the problem
Externí odkaz:
https://doaj.org/article/82985cff3d26404898aa8974049ee337
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-16 (2024)
Abstract Gait phase prediction is important in controlling assistive robotic devices such as exoskeletons, where the control unit must differentiate between gait phases to provide the necessary assistance when the user is wearing the exoskeleton. To
Externí odkaz:
https://doaj.org/article/0e7085a1f6cc4726b430a2b84f34d970