Zobrazeno 1 - 10
of 2 886
pro vyhledávání: '"decision fusion"'
Autor:
Jiping Wang, Chengqi Li, Bochao Zhang, Yunpeng Zhang, Lei Shi, Xiaojun Wang, Linfu Zhou, Daxi Xiong
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Approximately 75% of stroke survivors have movement dysfunction. Rehabilitation exercises are capable of improving physical coordination. They are mostly conducted in the home environment without guidance from therapists. It is impossible to
Externí odkaz:
https://doaj.org/article/b99c518f3d354fcc821667e35f6588ab
Autor:
S. Phani Praveen, Mohammad Kamrul Hasan, Siti Norul Huda Sheikh Abdullah, Uddagiri Sirisha, N. S. Koti Mani Kumar Tirumanadham, Shayla Islam, Fatima Rayan Awad Ahmed, Thowiba E. Ahmed, Ayman Afrin Noboni, Gabriel Avelino Sampedro, Chan Yeob Yeun, Taher M. Ghazal
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionGlobal Cardiovascular disease (CVD) is still one of the leading causes of death and requires the enhancement of diagnostic methods for the effective detection of early signs and prediction of the disease outcomes. The current diagnostic t
Externí odkaz:
https://doaj.org/article/261f8a01b402474884413969dc986db6
Publikováno v:
IEEE Access, Vol 12, Pp 137746-137759 (2024)
The safety and ride comfort of the emergency rescue vehicle can be improved greatly when the prior knowledge of the terrain in front of the vehicle is used as the active suspension input. In this paper, we present a robust and precise terrain preview
Externí odkaz:
https://doaj.org/article/e071cfbfc22c49bc80c951f0880deb8f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11839-11856 (2024)
Building information serves as a critical foundational dataset in the fields of urban planning, smart cities and surveying and mapping, and high-resolution remote sensing (HRRS) imagery has become a vital data source for extracting building informati
Externí odkaz:
https://doaj.org/article/cba6f1a3df74413fb933cc26b415160e
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7738-7747 (2024)
Fine-grained radar target classification based on single-band, such as wideband or narrowband, poses challenges even when utilizing deep learning methods. Since different bands reflect distinct characteristics of the targets, we focus on the fine-gra
Externí odkaz:
https://doaj.org/article/b1cbc802ae404a9a9ba7ee363dabd945
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3799-3820 (2024)
Hitherto, image-level classification on remote sensing landslide images has been paid attention to, but the accuracy of traditional deep learning-based methods still have room for improvement. The evidence theory is found efficient to boost the accur
Externí odkaz:
https://doaj.org/article/73461898763e459993ec07e871beb91a
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 185-201 (2024)
Low-complexity fusion rules relying on hybrid combining are proposed for decision fusion in frequency selective millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) sensor networks (SNs). Both centralized (C-MIMO) and distributed (D
Externí odkaz:
https://doaj.org/article/0ef0a7dc19f94bab85db1a12c20494e1
Publikováno v:
Jordanian Journal of Computers and Information Technology, Vol 9, Iss 4, Pp 347-359 (2023)
ABSTRACT In various applications of radar imagery, one of the fundamental problems is mainly linked to the analysis and interpretation of the images provided, in particular the recognition of moving and/or fixed targets. This task has become more dif
Externí odkaz:
https://doaj.org/article/df771e295fed47b99330a4dd47140318
Publikováno v:
Remote Sensing, Vol 16, Iss 22, p 4317 (2024)
With the development of sensor technology, the sources of remotely sensed image data for the same region are becoming increasingly diverse. Unlike single-source remote sensing image data, multisource remote sensing image data can provide complementar
Externí odkaz:
https://doaj.org/article/39b5e628d29746679ad795a7f796ea19
Publikováno v:
Energies, Vol 17, Iss 18, p 4629 (2024)
In cold climates, ice formation on wind turbines causes power reduction produced by a wind farm. This paper introduces a framework to predict icing at the farm level based on our recently developed Temporal Convolutional Network prediction model for
Externí odkaz:
https://doaj.org/article/2c98c80af88c465db74d6f50dfa11909