Zobrazeno 1 - 10
of 349
pro vyhledávání: '"dual attention mechanism"'
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:
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:
Remote Sensing, Vol 16, Iss 23, p 4441 (2024)
Spectral information plays a crucial role in fractional vegetation cover (FVC) estimation, and selecting the appropriate spectral information is essential for improving the accuracy of FVC estimation. Traditionally, spectral feature selection is prim
Externí odkaz:
https://doaj.org/article/5c69d1c45cbb4d0e820865f826817300
Publikováno v:
Applied Sciences, Vol 14, Iss 22, p 10515 (2024)
The rise of mobile communication, low-power chips, and the Internet of Things has made smartwatches increasingly popular. Equipped with inertial measurement units (IMUs), these devices can recognize user activities through artificial intelligence (AI
Externí odkaz:
https://doaj.org/article/834b8435b13a4c7290ef825f8c8d285d
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 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 Access, Vol 12, Pp 81911-81924 (2024)
Addressing the challenge of surface defect detection in load-bearing rails within auto-motive assembly workshops, which operate in complex environments and under long-term service, this paper proposes an innovative detection framework based on an imp
Externí odkaz:
https://doaj.org/article/42732b22aacd4c7a8d14ab2cfcc34153
Publikováno v:
Gong-kuang zidonghua, Vol 49, Iss 12, Pp 56-62 (2023)
Foreign objects mixed in during coal mining may cause accidents such as blockage or even tearing of conveyor belt connections. Most existing machine learning algorithms for coal flow foreign objects use supervised learning to automatically recoginze
Externí odkaz:
https://doaj.org/article/48c2c96d62b14619a270aaa633dbf5e6
Publikováno v:
Applied Sciences, Vol 14, Iss 19, p 9141 (2024)
With the passage of time, the constant changes in relevant factors, and the daily maintenance of tailings ponds, the difficulty of tailings pond safety management is increasing day by day. In order to systematically improve the early warning ability
Externí odkaz:
https://doaj.org/article/f0df7a9880724fe8bfbdc4e4c98370e4