Face detection and location technique is a hot research direction during recent years. Especially, driver face detection on highway is still a challenging problem in social safty deserving research. This paper propose...
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Face detection and location technique is a hot research direction during recent years. Especially, driver face detection on highway is still a challenging problem in social safty deserving research. This paper proposes a novel algorithm based on the improved Multi-task Cascaded Convolutional Networks(MTCNN) and Support Vector Machine(SVM) to realize accurate face region detection and feature location of driver's face on highway, predicting face and feature location via a coarse-to-fine pattern. The proposed algorithm is verified under various complex highway conditions. Experimental results show that the proposed model shows satisfied performance compared to other state-of-the-art techniques used in driver face detection and alignment, keeping robust to the occlusions, varying pose and extreme illumination on highway.
In this paper, we present a simple image depth level estimation algorithm. From the dark channel prior theory, an estimate of the air transmittance in the image is calculated. In wild surveillance, the disparity in th...
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In this paper, we present a simple image depth level estimation algorithm. From the dark channel prior theory, an estimate of the air transmittance in the image is calculated. In wild surveillance, the disparity in the image poses a huge challenge for smoke detection and other video analysis tasks. Appropriate depth level estimation provide significant prior knowledge for subsequent identification and detection. For landscape images, we can approximate the air transmittance to depth information for histogram analysis. The depth value is segmented by a multi-threshold segmentation algorithm, and the resulting image can be used for forest fireworks detection and the like. This method does not rely on samples and classifiers, and the algorithm does not require training. The final experimental results show that the depth level estimation of a single landscape image based on the dark channel prior can achieve good results.
Network-based wind speed forecasting has played an important role in the power system. The network parameters optimization is an important issue, and different optimization algorithms are believed to result in differe...
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Network-based wind speed forecasting has played an important role in the power system. The network parameters optimization is an important issue, and different optimization algorithms are believed to result in different forecasting accuracies. In this paper, six network parameters optimization algorithms, including Gradient descent, Momentum, Ada Grad, RMSprop, Adam, and Adadelta, are implemented and compared in the application of wind speed forecasting. As a case study, this paper uses a wind speed data obtained from Ningxia, China. The performance is evaluated by three metrics, namely, mean absolute error（MAE）, root mean square error（RMSE）, and mean absolute percentage error（MAPE）. The experiment results show that, Adam algorithm and RMSprop algorithm achieve better forecasting accuracy and less training time than the other optimization algorithms. This study can be a guide to the selection of optimization algorithms on wind speed forecasting problems for researchers.
Background: systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, ...
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Purpose-The paper aims to build the connections between game theory and the resource allocation problem with general *** proposes modeling the distributed resource allocation problem by Bayesian *** this paper,three b...
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Purpose-The paper aims to build the connections between game theory and the resource allocation problem with general *** proposes modeling the distributed resource allocation problem by Bayesian *** this paper,three basic kinds of uncertainties are ***,the purpose of this paper is to build the connections between game theory and the resource allocation problem with general ***/methodology/approach-In this paper,the Bayesian game is proposed for modeling the resource allocation problem with *** basic game theoretical model contains three parts:agents,utility function,and decision-making ***,the probabilistic weighted Shapley value(WSV)is applied to design the utility function of the *** achieving the Bayesian Nash equilibrium point,the rational learning method is introduced for optimizing the decision-making process of the ***-The paper provides empirical insights about how the game theoretical model deals with the resource allocation problem uncertainty.A probabilistic WSV function was proposed to design the utility function of ***,the rational learning was used to optimize the decision-making process of agents for achieving Bayesian Nash equilibrium *** comparing with the models with full information,the simulation results illustrated the effectiveness of the Bayesian game theoretical methods for the resource allocation problem under ***/value-This paper designs a Bayesian theoretical model for the resource allocation problem under *** relationships between the Bayesian game and the resource allocation problem are discussed.
This paper investigates a finite-time disturbance observer（FTDO） based nonsingular terminal sliding mode control（NTSMC） approach for DC-DC boost converter *** using exact feedback linearization theory and control ...
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ISBN:
(纸本)9781538629185
This paper investigates a finite-time disturbance observer（FTDO） based nonsingular terminal sliding mode control（NTSMC） approach for DC-DC boost converter *** using exact feedback linearization theory and control method to solve the output voltage regulation problem under the load resistance changes and external input voltage *** the disturbance estimated by FTDO into the design of the nonlinear dynamic sliding mode surface,a finite-time NTSMC method is developed to reject the effects of mismatched disturbances and achieve finite-time tracking *** compared with the nominal NTSMC method,the proposed method obtains a better disturbance rejection ability no matter the disturbances satisfy the matching condition or *** is shown that the stability of closed-loop system can be guaranteed by the proposed *** comparison results are displayed to demonstrate the robustness of the proposed controller against input voltage variations and load uncertainties.
In this paper, a method of tank gun stability control system based on multi-dimensional Taylor network optimal control(MTN) is proposed. As the fact that tank itself has a strong nonlinear characteris
ISBN:
(纸本)9781467389808
In this paper, a method of tank gun stability control system based on multi-dimensional Taylor network optimal control(MTN) is proposed. As the fact that tank itself has a strong nonlinear characteris
Ships stability and safety are always threatened by the unavoidable sway in the complicated situation of the sea, *** wind and roaring waves. Ensuring the stability of the ship as a difficult t
ISBN:
(纸本)9781467389808
Ships stability and safety are always threatened by the unavoidable sway in the complicated situation of the sea, *** wind and roaring waves. Ensuring the stability of the ship as a difficult t
This paper analyzes the contraction of the primaldual gradient optimization via contraction theory in the context of discrete-time updating dynamics. The contraction theory based on Riemannian manifolds is first estab...
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This paper develops a distributed model predictive control (DMPC) strategy for a class of discrete-time linear systems with consideration of globally coupled constraints. The DMPC under study is based on the dual prob...
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