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In order to realize autonomous landing of the unmanned aerial vehicle (UAV) in power patrolling, a visual method vision based on Faster Regions with Convolutional Neural Network (Faster R-CNN) for UAVs is studied. In this paper, we design the landing sign of the combination of concentric circles and pentagon, and propose the Faster R-CNN recognition algorithm which can be used to identify the target...
The commonly existing employed centralized algorithms fail to be adaptive to the new storage pattern on mobile edge cloud. To address this issue, we propose an alternating-direction-method-of-multipliers-based collaborative storage algorithm called MECCAS (Mobile Edge Cloud Collaborative Storage). The proposed MECCAS is able to minimize the delay of task execution and total costs for the overall operation,...
There are some common problems, such as low location accuracy and low sampling efficiency, existing in the present node localization algorithms that are based on Monte Carlo Localization (MCL) in mobile wireless sensor networks. To improve these issues, a Monte Carlo box localization algorithm based on RSSI(MCBBR) is proposed in this paper. In the algorithm, sampling box was constructed through RSSI...
Time synchronization is one of the fundamental techniques for the wireless sensor networks to obtain the real-time effective information. The security of this technology is becoming increasingly important. In this paper, we analyze the security of RBS, the synchronization algorithm in WSN, point out the potential vulnerabilities existing in the algorithm, and propose optimization on security for the...
This paper studies on how to improve the efficiency of multilayer relationship checking, which was the most complex and time-consuming operation in land plan spatial data quality checking. The existing researches on spatial data quality mostly focused on how to evaluate spatial data quality, but few studies on efficiency. With an in depth study on the characteristics of multilayer relationship, we...
In recent years, multi-class SVM has been one of the hot spots for many researchers, and multi-class classification based on clustering is one of strategies. Because the information of class-labels is not considered by clustering, too much branches of the binary-tree are formed, especially in the case of samples in different classes having similar features. To solve the problem, linear discriminant...
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