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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...
This paper presents an intelligent operation and maintenance training system for power grid operation staff of substation based on augmented reality (AR), whose functions, characteristics, software configuration and implementation are introduced in details. As the training and examination system for operation and maintenance personnel, the system was composed of intelligent training system and intelligent...
This letter presents a novel learning-based method called extreme learning machine (ELM) to solve the Bragg wavelength detection problem in the fiber Bragg grating (FBG) sensor network. Based on building up a regression model, the proposed approach is divided into two phases: 1) offline training phase and 2) online detection phase. Due to the good generalization capability of ELM, the well-trained...
For the urgent need of storm forecasting and warning, we achieved the rainstorm case retrieve system for the first time. We extracted the rainstorm radar image's features from historical data set by using digital image processing technology, reduced the unwanted attributes, mined the minimum decision rules according to rough set theory, formed rainstorm knowledge base and case base, and achieved the...
Focusing on the deficiencies of the existing IRT parameter estimation algorithm, the Resilient Back propagation algorithm and variable learning rate learning algorithm are used in the basis of artificial neural network algorithm to improve the network convergence speed, and the genetic algorithm is used to solve the local minima problem, then the improved BP algorithm is generated. Finally, the standard...
This paper presents an algorithm based on the ideas of bag of words and sparse representation for action recognition. We assume that all action instances form an action space and all action instances from one action class form a subspace of it. Furthermore, the action space can be represented by an over complete basis and each action instance can be represented by a linear combination of the basis...
In order to predict the influence of earthquake on building and buried pipeline, predictive model is constructed on the basis of artificial neural network (ANN). According to double parallel feed-forward neutral network model, which is a basic model of Back Propagation (BP) network, predictive model and calculating method are analyzed. The model is applied to the calculation of earthquake affecting...
In this paper we propose a weighted version of recently developed least squares twin support vector machine (LSTSVM) for pattern classification, in which different weights are put on the error variables in order to eliminate the impact of noise data and obtain the robust estimation. Here, we offer the formulations of the proposed weighted LSTSVM (WLSTSVM) in both linear and nonlinear cases. Comparative...
Recently, LSTSVM as a new binary SVM classifier based on nonparallel twin hyperplanes has shown a good classification performance, but the research on multi-class classification has still rarely been reported. In this paper, a multi-class LSTSVM classifier based on optimal directed acyclic graph is proposed. The idea of kernel parameter choice is used to realize the class separability criterion, an...
Several structures of artificial neural networks (ANNs) with different training patterns were investigated so as to compare their performances on detecting the cluster of microcalcifications (CM) on mammography. 150 region-of-interests (ROIs) around mass containing both positive and negative microcalcifications were selected for training the network by a standard or modified error-back-propagation...
Information on the vehicular traffic density in an intelligent transport system (ITS) is presently obtained mainly through loop detectors (LD), traffic radars and surveillance cameras. However, the difficulties and cost of installing loop detectors and traffic radars tend to be significant. Currently, a more advanced method of circumventing this is to develop a sort of virtual loop detector (VLD)...
This paper presents an algorithm based on the method of supervised machine learning and multi-keyframes to achieve markerless augmented reality (AR) application when there is a locally planar object in the scene. The main goal is to solve the problem of AR tracking in outdoor environment by only using vision and natural features. Instead of tracking fiducial markers, we track natural keypoints, during...
This study aimed to identify the stressors among sanitarian manpower in country and understand their influences on their well being and productivity. Study subjects came from Jiangsu, Shandong, Henan and Sichuan, for a total of 37 rural hospitals, 222 health care workers.Content analysis shows that employees suffered a range of work stress which was mostly uncontrollable and unavoidable. Negative...
Training a support vector machine (SVM) on a large-scale sample set is a challenging problem. This paper proposes a sample reduction strategy to pretreat training samples which is realized by a two step procedure: instance reduction and attribute reduction, and the classification model of the SVM is also offered. The experimental results show that the proposed reduction algorithm can effectively remove...
This paper presents the design and implementation of an intensive curriculum on embedded software design for university or college graduates of engineering background, who are seeking job opportunities in developing software for embedded system products. It is part of a government-conducted project intending to resolve the shortage of embedded software engineers in SoC (System-on-Chip) and related...
Based on multi-spectral digital image texture feature, a new method for discriminating tea categories was put forward. The images which have three waveband images (Red, Green, NIR) were recorded by multi-spectral digital imager (MS3100). Eight filters were designed based on discrete cosine transform (DCT), and the NIR image was processed by the 8 filters, then the Standard deviation (Sd) of original...
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