Zobrazeno 1 - 10
of 377
pro vyhledávání: '"weighted ensemble"'
Autor:
Jonathan Donhauser, Anna Doménech-Pascual, Xingguo Han, Karen Jordaan, Jean-Baptiste Ramond, Aline Frossard, Anna M. Romaní, Anders Priemé
Publikováno v:
Ecological Informatics, Vol 83, Iss , Pp 102817- (2024)
We present a comprehensive, customizable workflow for inferring prokaryotic phenotypic traits from marker gene sequences and modelling the relationships between these traits and environmental factors, thus overcoming the limited ecological interpreta
Externí odkaz:
https://doaj.org/article/753adbeed0da41b3b05154569898af9f
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 133, Iss , Pp 104123- (2024)
Forest canopy height (FCH) is crucial for monitoring forest structure and aboveground biomass. Light detecting and ranging (LiDAR), as a promising remote sensing technology, provides various forms of data for measuring and mapping FCH. Airborne laser
Externí odkaz:
https://doaj.org/article/a897296e255c45e3b7bc716cb4fcafea
Autor:
Roopesh Kumar Polaganga, Qilian Liang
Publikováno v:
Machine Learning with Applications, Vol 17, Iss , Pp 100564- (2024)
In the rapidly evolving realm of telecommunications, Machine Learning (ML) stands as a key driver for intelligent 6 G networks, leveraging diverse datasets to optimize real-time network parameters. This transition seamlessly extends from 4 G LTE and
Externí odkaz:
https://doaj.org/article/39f8f78fb7e44d7dbb36a92dac97301c
Publikováno v:
IEEE Access, Vol 12, Pp 127614-127628 (2024)
Accurate classification of software requirements, distinguishing between functional and non-functional aspects, is crucial for developing reliable and efficient software systems. However, existing methods often struggle with insufficient semantic und
Externí odkaz:
https://doaj.org/article/e63f02ad428c4493b35903698a71d1db
Autor:
Hossein Ahmadi, Luca Mesin
Publikováno v:
IEEE Access, Vol 12, Pp 103626-103646 (2024)
Electroencephalography (EEG) based Brain-Computer Interfaces (BCIs) are vital for various applications, yet achieving accurate EEG signal classification, particularly for Motor Imagery (MI) tasks, remains a significant challenge. This study introduce
Externí odkaz:
https://doaj.org/article/b0d452233918432d95b18174ccdbe0b2
Publikováno v:
Geoscience Letters, Vol 11, Iss 1, Pp 1-13 (2024)
Abstract Under the proposal of “seamless forecasting”, it has become a key problem for meteorologists to improve the skills of subseasonal forecasts. Since the launch of the subseasonal-to-seasonal (S2S) plan by WMO, the precision of model predic
Externí odkaz:
https://doaj.org/article/b31ee16379ad4578abb9e53efa4bd823
Publikováno v:
IEEE Access, Vol 12, Pp 5731-5742 (2024)
Knee osteoporosis (KOP) is a skeletal disorder characterized by bone tissue degradation and low bone density, leading to a high risk of bone fractures in the knee area. The traditional method for identifying knee osteoporosis is knee radiography, whi
Externí odkaz:
https://doaj.org/article/f3fb71c9e77b4e138fcecf978c15b70a
Publikováno v:
Journal of Communications Software and Systems, Vol 19, Iss 4, Pp 299-307 (2023)
Nowadays, the proliferation of social media and e-commerce platforms is largely due to the development of internet technology. Additionally, consumers are used to the idea of using these platforms to share their thoughts and feelings with others thro
Externí odkaz:
https://doaj.org/article/11b667396e994a5b8182141449e5e8dd
Publikováno v:
Agronomy, Vol 14, Iss 4, p 777 (2024)
One of the crucial research areas in agricultural decision-making processes is crop yield prediction. This study leverages the advantages of hybrid models to address the complex interplay of genetic, environmental, and management factors to achieve m
Externí odkaz:
https://doaj.org/article/8da6b4f999a3459285a5e43260909e32
Autor:
Dong-Wan Kang, Gi-Hun Park, Wi-Sun Ryu, Dawid Schellingerhout, Museong Kim, Yong Soo Kim, Chan-Young Park, Keon-Joo Lee, Moon-Ku Han, Han-Gil Jeong, Dong-Eog Kim
Publikováno v:
Frontiers in Neurology, Vol 14 (2023)
Background and purposeMultiple attempts at intracranial hemorrhage (ICH) detection using deep-learning techniques have been plagued by clinical failures. We aimed to compare the performance of a deep-learning algorithm for ICH detection trained on st
Externí odkaz:
https://doaj.org/article/5b0897498a2647a29c16f53be079fd6b