|
|
|
|
|
Anderson Carvalho, Daniel Riordan and Joseph Walsh
This study presents a newly developed edge computing platform designed to enhance connectivity between edge devices and the cloud in the agricultural sector. Addressing the challenge of synchronizing a central database across 850 remote farm locations in...
ver más
|
|
|
|
|
|
|
|
|
Xiaokai Sun, Baoyun Guo, Cailin Li, Na Sun, Yue Wang and Yukai Yao
In urban point cloud scenarios, due to the diversity of different feature types, it becomes a primary challenge to effectively obtain point clouds of building categories from urban point clouds. Therefore, this paper proposes the Enhanced Local Feature A...
ver más
|
|
|
|
|
|
|
|
|
Chinyang Henry Tseng, Woei-Jiunn Tsaur and Yueh-Mao Shen
In detecting large-scale attacks, deep neural networks (DNNs) are an effective approach based on high-quality training data samples. Feature selection and feature extraction are the primary approaches for data quality enhancement for high-accuracy intrus...
ver más
|
|
|
|
|
|
|
|
|
Bing Su and Jiwu Liang
With the innovation of wireless communication technology and the surge of data in mobile networks, traditional routing strategies need to be improved. Given the shortcomings of existing opportunistic routing strategies in transmission performance and sec...
ver más
|
|
|
|
|
|
|
|
|
Hossein Salehi, Saeid Gharechelou, Saeed Golian, Mohammadreza Ranjbari and Babak Ghazi
Hydrological modeling is essential for runoff simulations in line with climate studies, especially in remote areas with data scarcity. Advancements in climatic precipitation datasets have improved the accuracy of hydrological modeling. This research aims...
ver más
|
|
|
|