Zobrazeno 1 - 10
of 7 526
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
Autor:
Shizhe Yuan, Li Zhou
Publikováno v:
Alexandria Engineering Journal, Vol 112, Iss , Pp 585-597 (2025)
With the advancement of artificial intelligence, 3D human pose estimation-based systems for sports training and posture correction have gained significant attention in adolescent sports. However, existing methods face challenges in handling complex m
Externí odkaz:
https://doaj.org/article/aeb10f7f76ab4335a4767583852e16b8
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-19 (2024)
Abstract Accurate forecasting of traffic flow in the future period is very important for planning traffic routes and alleviating traffic congestion. However, traffic flow forecasting still faces serious challenges. Most of the existing traffic flow f
Externí odkaz:
https://doaj.org/article/6e432fa04ff841b582643a7e2f79cf59
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-36 (2024)
Abstract This survey overviews recent Graph Convolutional Networks (GCN) advancements, highlighting their growing significance across various tasks and applications. It underscores the need for efficient hardware architectures to support the widespre
Externí odkaz:
https://doaj.org/article/ffad888138d7431c98da43eb466bf6d5
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:
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
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