Zobrazeno 1 - 10
of 14 814
pro vyhledávání: '"Convolutional Network"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 853-864 (2025)
Semantic segmentation of aerial images is crucial yet resource-intensive. Inspired by human ability to learn rapidly, few-shot semantic segmentation offers a promising solution by utilizing limited labeled data for efficient model training and genera
Externí odkaz:
https://doaj.org/article/aaaca3a28fe34d469546abc6e7f38aef
Autor:
Peihao Yang, Guodong Ye
Publikováno v:
Alexandria Engineering Journal, Vol 111, Iss , Pp 432-445 (2025)
Tropical Cyclones (TCs) are highly destructive weather phenomena that can cause significant social and economic damage. With the development of meteorological monitoring technology and the updating of database, accurately forecasting the track of TC
Externí odkaz:
https://doaj.org/article/8ed2abd776cc43b0a9fc7d06d0cbf2b2
Publikováno v:
Emerging Science Journal, Vol 8, Iss 6, Pp 2554-2569 (2024)
Visual Speech Recognition (VSR), commonly referred to as automated lip-reading, is an emerging technology that interprets speech by visually analyzing lip movements. A challenge in VSR where visually distinct words produce similar lip movements is kn
Externí odkaz:
https://doaj.org/article/184428b4cbec4b46b552ec048f0f78e6
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-24 (2024)
Abstract Multimodal brain network analysis enables a comprehensive understanding of neurological disorders by integrating information from multiple neuroimaging modalities. However, existing methods often struggle to effectively model the complex str
Externí odkaz:
https://doaj.org/article/0735d99e13194d539931a11c5f1b7150
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract With the exponential growth of mobile devices and data traffic, mobile edge computing has become a promising technology, and the placement of edge servers plays a key role in providing efficient and low-latency services. In this paper, we in
Externí odkaz:
https://doaj.org/article/1f8d6e72af5f4d8db0619c7b6009e9b6
Autor:
Leonardo Daou, Eileen Marie Hanna
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 3595-3609 (2024)
Protein complexes are groups of interacting proteins that are central to multiple biological processes. Studying protein complexes can enhance our understanding of cellular functions and malfunctions and thus support the development of effective dise
Externí odkaz:
https://doaj.org/article/bc8a5f8c29604f67b5f27e92b49337b0
Publikováno v:
工程科学学报, Vol 46, Iss 12, Pp 2297-2306 (2024)
The paper proposes a method based on kernel principal component analysis (KPCA) and multi-scale temporal convolution network (MTCN) for identifying faults in lithium-ion batteries, which is crucial for ensuring the safe and stable operation of energy
Externí odkaz:
https://doaj.org/article/eff77fe81201428b9f365f24aca22414
Publikováno v:
Alexandria Engineering Journal, Vol 109, Iss , Pp 144-156 (2024)
Human pose estimation in sports training is a critical application within Internet of Things (IoT) environments, leveraging IoT devices to enhance performance analysis and injury prevention. Current methods struggle with real-time processing and accu
Externí odkaz:
https://doaj.org/article/0fe00ec260a046cf8a284c555d206504
Publikováno v:
Journal of Applied Animal Research, Vol 52, Iss 1, Pp 1-13 (2024)
ABSTRACTLivestock behavior is related to the healthy breeding and welfare level. Therefore, monitoring the behavior of sheep is helpful to predict the health status of sheep and thus safeguard the production performance of sheep. Taking semi-housed s
Externí odkaz:
https://doaj.org/article/c1783559f86a429ebba2c7dfb005b5f7
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1016-1025 (2024)
Geometric deep learning has demonstrated a great potential in non-Euclidean data analysis. The incorporation of geometric insights into learning architecture is vital to its success. Here we propose a curvature-enhanced graph convolutional network (C
Externí odkaz:
https://doaj.org/article/b0ab56dcde6e4749a5f5ca0c626a9748