Zobrazeno 1 - 10
of 1 104
pro vyhledávání: '"dual-attention"'
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-12 (2024)
Abstract Document-level relation extraction (RE), which requires integrating and reasoning information to identify multiple possible relations among entities. However, previous research typically performed reasoning on heterogeneous graphs and set a
Externí odkaz:
https://doaj.org/article/d236cbfc53d34c67a13a168364e20e08
Publikováno v:
Alexandria Engineering Journal, Vol 114, Iss , Pp 543-555 (2025)
With the rise of artificial intelligence approaches, fully automatic tooth segmentation models from Cone-beam Computed Tomography (CBCT) images become more popular for dental clinical diagnosis. Recently, many deep learning-based tooth segmentation t
Externí odkaz:
https://doaj.org/article/371c2e300caa4be89dadb60b94bce150
Publikováno v:
Alexandria Engineering Journal, Vol 111, Iss , Pp 123-135 (2025)
In the field of autonomous driving, the accuracy and real-time requirements for 3D object detection technology continue to improve, which is directly related to the commercialization process and market popularity of autonomous vehicles. Despite the e
Externí odkaz:
https://doaj.org/article/b6e4d613179449f592b81df1d32ee29e
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
In marine ranching aquaculture, dissolved oxygen (DO) is a crucial parameter that directly impacts the survival, growth, and profitability of cultured organisms. To effectively guide the early warning and regulation of DO in aquaculture waters, this
Externí odkaz:
https://doaj.org/article/8b3c48be33f749bab865362fb01014fd
Publikováno v:
IEEE Access, Vol 12, Pp 173618-173637 (2024)
Stock price forecasting is a critical component of financial market analysis and plays a key role in formulating investment strategies, affecting a wide range of stakeholders. To address the inherent complexities and dynamic fluctuations in stock pri
Externí odkaz:
https://doaj.org/article/593f7aefc4234235a161966fe50f37dd
Publikováno v:
IEEE Access, Vol 12, Pp 146587-146597 (2024)
Due to the absorption and scattering of light by suspended particles, underwater images may suffer from color casts, low contrast, and blurred texture details. Traditional statistics-based and physical model-based methods have improved image quality
Externí odkaz:
https://doaj.org/article/9355d33e9a974526801d2b3c7cbbd033
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 15494-15511 (2024)
Hyperspectral image (HSI) reconstruction plays a crucial role in compressive spectral imaging with coded aperture snapshot spectrometry. Although HSI reconstruction has attracted much attention in recent years, it remains a challenging problem. Exist
Externí odkaz:
https://doaj.org/article/ced36e48ae8140649941e28584caf849
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14726-14741 (2024)
Although many scholars have realized that deep learning methods have great advantages in hyperspectral lithology classification now, most of them use simple convolutional neural networks for discussion, which are difficult to effectively extract spec
Externí odkaz:
https://doaj.org/article/604d781a88b74b9ebacfb008d6a944ea
Autor:
Talabathula Jayanth, A. Manimaran
Publikováno v:
IEEE Access, Vol 12, Pp 114760-114785 (2024)
Financial market prediction has shown considerable potential in the past few years from the combination of contemporary Deep Learning (DL) techniques and traditional time series forecasting methodologies. To predict the stock prices of three distinct
Externí odkaz:
https://doaj.org/article/0a4de0baedcc4b7680e05655b5ab533d
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10842-10861 (2024)
Due to the interference of multiplicative speckles, it is challenging to accurately detect changes in polarimetric synthetic aperture radar (PolSAR) images. Convolutional neural network has been proven to learn rich local features from PolSAR data. H
Externí odkaz:
https://doaj.org/article/441926ce1f23407f9def3a482d32dcd7