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Titlebook: Intelligent Data Analysis and Applications; Proceedings of the T Jeng-Shyang Pan,Václav Sná?el,Xiao Dong Wang Conference proceedings 2017 S

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21#
發(fā)表于 2025-3-25 07:11:49 | 只看該作者
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發(fā)表于 2025-3-25 09:28:34 | 只看該作者
The Reliability and Economic Analysis Comparison Between Parallel System and Erlang Distribution Sysmponent to achieve it, but taking redundant backup, it needs to increase the system detection equipment and switch parts is necessary, which is a significant increase in the cost of the system, in the other hand, when we taking parallel system, it will reduce the cost, but also reduce the reliabilit
23#
發(fā)表于 2025-3-25 14:12:28 | 只看該作者
Research on the Construction of College Information Applications Based on Cloud Computingayer. Then reformed the system structure of the educational management system, proposed the resource scheduling strategy for the cloud platform, the experimental and operating results showed that the dynamic elastic extension properties of the cloud platform greatly improve the performance of educat
24#
發(fā)表于 2025-3-25 17:49:29 | 只看該作者
25#
發(fā)表于 2025-3-25 22:02:50 | 只看該作者
Image Classification Based on Image Hash Convolution Neural Networkr, for massive amounts of data, calculation and storage is a big bottleneck. In this paper, a method named image hash was proposed to solve this problem. Image hash can code high-dimensional image feature for simple binary code. Feature extraction is the most important step in image hash. In the cur
26#
發(fā)表于 2025-3-26 00:40:26 | 只看該作者
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發(fā)表于 2025-3-26 05:16:15 | 只看該作者
28#
發(fā)表于 2025-3-26 11:14:03 | 只看該作者
29#
發(fā)表于 2025-3-26 15:52:40 | 只看該作者
A New Method for Extraction of Residential Areas from Multispectral Satellite Imageryesidential areas noises such as vegetation regions, shadows and water areas are removed. Second, the preprocessed image is classified into two categories by texture features: residential areas class and non-residential areas class. Finally, the residential areas class is refined by using a series of
30#
發(fā)表于 2025-3-26 20:31:58 | 只看該作者
Tooth Segmentation from Cone Beam Computed Tomography Images Using the Identified Root Canal and Haranal centerline identified by graph theory based energy minimization problem is applied as prior knowledge aiding for the segmentation. Besides, though we use the idea of contour tracking strategy as adopted by most published methods based on slice-by-slice basis, within a slice, the segmentation is
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