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Tattoo Recognition Based on Triplet GAN

Tattoo Recognition Based on Triplet GAN

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第37届中国控制会议

作者： Cao Jiawang Zhu Yuan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

An important feature of the deep learning algorithm is that the hidden layer of the neural network is more dependent on more computing resources and a larger amount of data. In this paper, we use Triplet GAN method to identify human body images with tattoos using fewer data sample labels. The model achieved better results（0.9462） than the only Triplet（0.8352） and only GAN（0.9178） in the MNIST dataset, it also achieved higher recognition accuracy（77-82%） under the premise of saving the amount of data, compared with the traditional machine learning algorithm（54-84%）. We provide a new idea for tattoo image recognition applications in embedded computing units.

关键词： Tattoo Recognition Triplet GAN Embedded Computing Units

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Finite-time H∞ state estimation for discrete time-delayed stochastic switched genetic regulatory networks with uncertain sojourn probabilities

Finite-time H∞ state estimation for discrete time-delayed s...

引用

第37届中国控制会议

作者： REN Chuanyu WAN Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the problem of finite-time H∞ state estimation for discrete-time stochastic switched genetic regulatory networks（GRNs） with time-varying delays and exogenous disturbances. A new discrete time-delayed stochastic switched GRN model with uncertain sojourn probabilities is devised, which is more general than the switched GRNs model with completely known sojourn probabilities. The sufficient conditions which guarantee the stochastic finite-time boundedness of the estimation error dynamics with a prescribed H∞ disturbance attenuation level are derived. By solving several matrix inequalities,the state estimator parameters can be obtained. A numerical example is given to illustrate the effectiveness of our results.

关键词： Genetic regulatory networks（GRNs） Finite-time H∞ state estimation Uncertain sojourn probabilities

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On Overvoltage Intrusion Detection System for Substations

On Overvoltage Intrusion Detection System for Substations

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Chinese control Conference (CCC)

作者： Tao Zhao Yongbo Li Jing Rao Zhongzhao Xie Zijia HU Rubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P.R.China

In the modern power system, overvoltage phenomenon occurs frequently. Overvoltage generation will cause electrical equipment breakdown, explosion, and other accidents. These accidents not only cause unnecessary economic losses but also seriously affect the operation of power system. The popularization and application of on-line monitoring technology for UHV AC and DC transmission lines provide a guarantee for the safe operation of the power grid. Monitoring the overvoltage intrusion of UHV substations and accurately recording the parameters of overvoltage intrusion is of great significance to the study of overvoltage and the protection of over-voltage in substations. Based on the analysis of the principle of a monitoring system, this paper puts forward the mathematical model of a monitoring system. According to the basic functions of a monitoring system, it puts forward the overall design plan combining the upper computer and the lower computer, and the key problems to be solved in the monitoring system. Including the board design and the high speed data acquisition board based on FPGA design of control system based on STM32, and the automatic variable rate compression technology, GPS timing and Timekeeping Technology, overvoltage invasion wave trigger judgment, high speed data acquisition and cache technology and based on TCP protocol according to the number of batch transmission.

关键词： Voltage control Monitoring Power systems Data acquisition Intrusion detection Global Positioning System Hardware

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A Safety Assessment Method Based on Online Sequential Extreme Learning Machine（OS-ELM） in Deep Drilling Process

A Safety Assessment Method Based on Online Sequential Extrem...

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第37届中国控制会议

作者： Yupeng Li Weihua Cao Chao Gan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Accurate and timely assessment of drilling system is key for achieving safety and efficiency in deep drilling. In this paper, an online assessment model is proposed by applying online sequential extreme learning machine（OS-ELM）. The model has been tested through the actual drilling data for drilling system safety assessment and accidents early warning. By analyzing the mechanism characteristics of accidents, well logging parameters are chosen as the input and accident types are chosen as the output. Owing to the OS-ELM is capable of updating network parameters based on new arriving data without retraining historical data, the model can be updated online for specific formation accidents information to make it more adaptable to a particular environment. The numerical test results show that, comparing with other widely used assessment techniques like support vector machines（SVM） and back propagation（BP）, the proposed model has a higher accuracy and shorter recognition time.

关键词： safety assessment extreme learning machine deep drilling online learning

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Position control of a Planar Four-Link Underactuated Manipulator

Position Control of a Planar Four-Link Underactuated Manipul...

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第37届中国控制会议

作者： Dong Liu Xuzhi Lai Yawu Wang Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A position control strategy by employing the model reduction and the cascade transformation is proposed for a planar four-link AAPA(Active-Active-Passive-Active) underactuated manipulator in this ***,a dynamics model of the system is ***,three controllers are designed based on the Lyapunov function to control the fourth active link from any initial angle to zero while the angles of the first and second active link remain their initial values,which makes the system is reduced to a planar virtual three-link AAP(Active-Active-Passive) underactuated ***,we obtain the new inputs of the cascade system of the planar virtual three-link AAP underactuated ***,we can get the controllers of the active links to realize the system position control *** results demonstrate the validity of the proposed control strategy.

关键词： Position control Model Reduction Cascade Transformation Underactuated Manipulator Lyapunov Function

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Improving Training-based Reflectance Reconstruction via White-balance and Link Function

Improving Training-based Reflectance Reconstruction via Whit...

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第37届中国控制会议

作者： Li-Jun Zhang Jun Jiang Hui Jiang Jing-Jing Zhang Xing Jin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

An improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance by inserting white balance and link function during the training-based method. The novelty in our method is the use of whitebalancing to normalize the scene illumination and link function to transform the reflectance, we use a radial basis function network to model the mapping between camera-specific RGB values and specific reflectance spectra. Experimental results indicate that the proposed method significantly outperforms currently existing methods in terms of spectral error and shape especially under the illumination not present in the training process.

关键词： Reflectance reconstruction Training-based White-balance Link function Radial basis function network

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On overvoltage intrusion detection system for substations

On overvoltage intrusion detection system for substations

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第37届中国控制会议

作者： Tao Zhao Yongbo Li Jing Rao Zhongzhao Xie Zijia Hu School of Automation China University of Geoscience Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

关键词： overvoltage on-line monitoring automatic transmission rate compression trigger judgment

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Fog Removal Method of Slope Monitoring Image Based On Vision Detection

Fog Removal Method of Slope Monitoring Image Based On Vision...

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第37届中国控制会议

作者： Xianzhen Sang Yue Yang Xianhe Hou School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the slope monitoring based on image detection,the main work is to process the acquired slope *** landslide occurred mostly in the rain,fog and other complex weather *** we can process effectively and fast fog images according to the fog horizon slope vision *** would be helpful for subsequent image segmentation,object extraction,positioning,and improving the accuracy and efficiency of detection of slope *** on the visual technology in slope monitoring,we compared two kinds of defogging algorithm of slope *** is a kind of image enhancement method of non-physical model,mainly including:equalization algorithm and homomorphic filtering algorithm,McCann Retinex algorithm and multi-scale Retinex algorithm and a global *** other is the image restoration method based on physical model,including the dark channel prior bilateral filtering algorithm,and combined with the theory of dark channel prior to fog *** experimental results show that the histogram equalization method has the advantage of fast imaging quality in slope visual image processing,and is more suitable for slope monitoring.

关键词： Slope monitoring Image processing Dark Channel Prior Bilateral filtering

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Dense Depth Estimation with Absolute Scale

Dense Depth Estimation with Absolute Scale

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第37届中国控制会议

作者： Xing Jin Zhiwen Yao Jingjing Zhang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Considering the difficulties in estimating depth from single image, in this paper, we propose a method to obtain the absolute scale depth map by combining the convolution neural network and depth filter. We compute relative transformation between consecutive frames by direct tracking features, which are extracted from RGB images and whose depthes are predicted by deep network, and then optimize relative motion by searching for a better feature alignment in epipolar line, and finally update every pixel depth of the reference frame by depth filter. We evaluate the proposed method on the open dataset comparison against the state of the art in depth estimation to evaluate our method.

关键词： Depth Estimation Pose Estimation Depth Filter

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A New Result on H∞ State Estimation of Delayed Static Neural Networks via Augmented Lyapunov-Krasovskii Functional

A New Result on H∞ State Estimation of Delayed Static Neura...

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第37届中国控制会议

作者： Zhenman Gao Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper,the problem on guaranteed H∞ performance state estimation for static neural networks with a timevarying delay is investigated and the corresponding criterion is ***,a novel augmented Lyapunov-Krasovskii functional(LKF) is *** the derivative of the LKF is estimated by the relaxed integral ***,the state estimator can be calculated by solving a set of linear matrix ***,an example is used to illustrate the effectiveness of the proposed method.

关键词： Static neural networks H∞ performance state estimation time-varying delay augmented LKF

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