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Chinese Automation Congress (CAC)

作者： Yani Wang Yangyang Liu Minyin Lu An-Min Zou College of Engineering Shantou University Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou China

With consideration of communication link attacks, the distributed predefined-time consensus control issue of multi-agent systems is studied. First, a distributed resilient predefined-time observer is introduced to obtain an exact estimation of the states of the leader within predefined time. Second, a predefined-time consensus control protocol is proposed. The rigorous proof demonstrates that all follower agents can reach a common state within predefined time. At last a numerical example is presented to show the effectiveness of the resilient predefined-time controller.

关键词： Measurement Protocols Automation Estimation Consensus control Observers Numerical simulation

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A Discrete-time Geo/G/1 Retrial Queue with Balking Customer, Second Optional Service, Bernoulli Vacation and General Retrial Time

A Discrete-time Geo/G/1 Retrial Queue with Balking Customer,...

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第七届模糊信息与工程国际会议(ICFIE'2014)、第一届运筹与管理国际会议 (ICORG'2014)暨中国运筹学会模糊信息与工程分会第七届年会、广东省运筹学会第二届年会、粤港澳运筹学会首届年会

作者： Yan Chen Li Cai Cai-min Wei Department of Natural Sciences Shantou Polytechnic Department of Mathematics Shantou University Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Techniques Shantou University

In this paper, we study a discrete-time Geo/G/1 retrial queue with a balking customer and a second optional service where retrial time follows a general distribution. If an arriving customer finds the server free, he begins the service immediately. If an arriving customer finds the server busy or to be on vacation, then he will consider whether he enters into the system. After a customer accepts his first essential service, he may leave the system or ask for a second *** this model, we assume that the server, after each service completion, may begin a vacation or wait to serve the following customer. This paper studies the Markov chain underlying this model,we establish the probability generating functions of the orbit size and system size. Finally, some performance measures and some numerical examples are presented.

关键词： retrial queue balking customer optional service Bernoulli vacation

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Automated steel bar counting and center localization with convolutional neural networks

arXiv

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arXiv 2019年

作者： Fan, Zhun Lu, Jiewei Qiu, Benzhang Jiang, Tao An, Kang Josephraj, Alex Noel Wei, Chuliang Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China

Automated steel bar counting and center localization plays an important role in the factory automation of steel bars. Traditional methods only focus on steel bar counting and their performances are often limited by complex industrial environments. Convolutional neural network (CNN), which has great capability to deal with complex tasks in challenging environments, is applied in this work. A framework called CNN-DC is proposed to achieve automated steel bar counting and center localization simultaneously. The proposed framework CNN-DC first detects the candidate center points with a deep CNN. Then an effective clustering algorithm named as Distance Clustering (DC) is proposed to cluster the candidate center points and locate the true centers of steel bars. The proposed CNN-DC can achieve 99.26% accuracy for steel bar counting and 4.1% center offset for center localization on the established steel bar dataset, which demonstrates that the proposed CNN-DC can perform well on automated steel bar counting and center localization. Code is made publicly available at: https://***/BenzhangQiu/Steel-bar-Detection. Copyright © 2019, The Authors. All rights reserved.

关键词： Clustering algorithms

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Automatic pavement crack detection based on structured prediction with the convolutional neural network

arXiv

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arXiv 2018年

作者： Fan, Zhun Wu, Yuming Lu, Jiewei Li, Wenji Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China

Automated pavement crack detection is a challenging task that has been researched for decades due to the complicated pavement conditions in real world. In this paper, a supervised method based on deep learning is proposed, which has the capability of dealing with different pavement conditions. Specifically, a convolutional neural network \(CNN\) is used to learn the structure of the cracks from raw images, without any preprocessing. Small patches are extracted from crack images as inputs to generate a large training database, a CNN is trained and crack detection is modeled as a multi-label classification problem. Typically, crack pixels are much fewer than non-crack pixels. To deal with the problem with severely imbalanced data, a strategy with modifying the ratio of positive to negative samples is proposed. The method is tested on two public databases and compared with five existing methods. Experimental results show that it outperforms the other methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Classification (of information)

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Improving the compression efficiency for transform video coding

Improving the compression efficiency for transform video cod...

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International Conference on Systems and Informatics (ICSAI)

作者： Jianyu Lin Department of Electronic Engineering Guangdong Provincial key Laboratory of Digital Signal and Image Processing Guangdong P. R. China

A new 3D transform video coding algorithm is introduced, which does not use motion compensation. More independent and highly efficient algorithms are employed for each key step of the transform coding. For the transform step, the SCWP (Spectral Condensed Wavelet Packet) is adopted. For the quantization step, a trimming process is implemented, which keeps the bit allocation function of the significant propagation technique but is independent from the entropy coding step. For the entropy coding step, a novel entropy coding technique based upon binary run-length coding is proposed. This binary entropy coding can be applied to multiple symbol source coding, and it approaches an optimal efficiency bound which is within 1.5% of the source entropy when the source approaches iid. Principally, the complexity of the proposed transform video coding algorithm is comparable to that of a 2D still image transform coding algorithm. However, its compression performance is competitive to HEVC at high compression bitrates.

关键词： image coding Bit rate Transforms Encoding Algorithm design and analysis Video coding Three-dimensional displays

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Multi-objective evolutionary algorithms embedded with machine learning — A survey

Multi-objective evolutionary algorithms embedded with machin...

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Congress on Evolutionary Computation

作者： Zhun Fan Kaiwen Hu Fang Li Yibiao Rong Wenji Li Huibiao Lin Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou University Guangdong Shantou Department of Electronic Engineering Shantou University Guangdong Shantou

Multi-objective evolutionary algorithms (MOEAs) have been widely used in solving multi-objective optimization problems. A great number of the-state-of-art MOEAs have been proposed. These MOEAs can be classified into the following categories: decomposition-based, domination-based, indicator-based, and probability-based methods. Among them, the first four categories belong to non-model based methods, while the fifth one is considered to be model-based method, in which machine learning techniques are often used to build the models. Recently, embedding machine learning mechanisms into MOEAs is becoming popular and promising. In this paper, a relatively thorough review on both traditional MOEAs and those equipped with machine learning mechanisms are made, with the aim of shedding light on the future development of this emerging research field.

关键词： Optimization Data models Vegetation Convergence Clustering algorithms Evolutionary computation Boosting

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MB-CapsNet: An Efficient Fusion of MobileNetV3 and Matrix Capsule Networks

MB-CapsNet: An Efficient Fusion of MobileNetV3 and Matrix Ca...

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Chinese Automation Congress (CAC)

作者： Wenxing Han An-Min Zou Dept. of Electronic and Information Engineering Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou University Shantou China

The capsule network constructs the relationship between the part and the whole in an image through feature coding, which shows excellent performance in the image classification. However, the original capsule network is weak in extracting useful feature information, because it tends to explain all the information in a graph and the advantages of the capsule network cannot be reflected in the face of complex background datasets. By using MobileNetV3 as the backbone to replace the simple primary convolutional network layer, an improved capsule network named MB-CapsNet is proposed in this paper. The advanced network reducing the interference of invalid features to focus on effective features. At the same time, a variety of parameter sets are employed and extensive experiments are proceeded on four kinds of datasets. After that, an optimal network configuration is obtained which is suitable for different datasets. The experimental results illustrate that the advanced MB-CapsNet is more effectively than the original capsule network in the feature extraction, showing its advantages and potential in complex datasets.

关键词： Sensitivity Convolution Neural networks Interference Routing Feature extraction Convolutional neural networks

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GPU-based Hybrid Parallel Logic Simulation for Scan Patterns

GPU-based Hybrid Parallel Logic Simulation for Scan Patterns

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International Test Conference in Asia (ITC-Asia)

作者： Liyang Lai Qiting Zhang Hans Tsai Wu-Tung Cheng Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Key Laboratory of Intelligent Manufacturing Technology Shantou University Shantou Guangdong China Mentor a Siemens Business Wilsonville OR US

ISBN: (数字)9781728189444

ISBN: (纸本)9781728189451

GPGPU, general-purpose computing on graphics processing units, has been witnessed growing from a niche to a mainstream computing paradigm in the last decade. It is widely deployed in machine learning, artificial intelligence, and many scientific applications. In this article, we study gate-level logic simulation for scan test patterns, one of the key algorithmic components for test generation, fault grading and design rule check. We are exploring if GPGPU can deliver scalable performance speedup as promised by its massive parallelism. We discuss the limitations of the state of art work. With GPUs' architectural features in mind, a novel algorithm of hybrid race-tolerant parallel logic simulation is proposed to unleash its immense power of parallelization. Its unique integration of oblivious simulation and event-driven simulation leads to a scalable realization of parallel logic simulation for scan patterns. For the first time in the literature, it is demonstrated that a modest GPU can handle an industrial design of over twenty million gates with excellent performance scalability.

关键词： Logic gates Integrated circuit modeling Computational modeling Graphics processing units Data models Instruction sets Circuit faults

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Synchronized 2D SLAM and 3D Mapping Based on Three Wheels Omni-directional Mobile Robot

Synchronized 2D SLAM and 3D Mapping Based on Three Wheels Om...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Sibo Huang Chong Li Zhaoquan Cai Guijie Zhu Li Yao Zhun Fan Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou China Huizhou University Huizhou China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In this paper, we design a three wheels Omni-directional mobile robot (TOMR) and propose a method of simultaneous construction of 2D and 3D maps based on the mobile robot. To be more specific, we use information from a laser and a kinect to build 2D grid maps and 3D environment, respectively. The particle filter algorithm is used to achieve the pose of the robot, together with the OctoMap which is generated from a 3D point cloud map, to construct the 2D and 3D maps. An asymmetric environment is employed to test our proposed method and some state-of-the-art methods like RGB-D SLAM and ORB-SLAM. The experimental results show that the proposed method is efficient for synchronized 2D and 3D mapping and has better performance than other compared algorithms.

关键词： Three-dimensional displays Mobile robots Two dimensional displays Robot kinematics Wheels Simultaneous localization and mapping

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Building 3D Map Based on Monte Carlo Localization and Feature Extraction

Building 3D Map Based on Monte Carlo Localization and Featur...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Zhun Fan Ying Chen Chong Li Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou Guangdong China School of Electrical and Information Engineering Shantou University Shantou Guangdong China

ISBN: (数字)9781728190105

ISBN: (纸本)9781728190112

In this project, we mainly explore and construct the 3D indoor map. The goal of this paper is to merge the data from the laser and kinect sensor with Monte Carlo Location(MCL) in 2D map. We use the laser range sensor to construct the 2D map and get the robot's pose transformation matrix. Then, we obtain the color and depth image by using the kinect sensor and build 3D point cloud map by using the feature extraction method, getting the kinect's pose transformation matrix. After that, we get the optimal pose transformation by using the Kalman Filter to calibrate the robot's pose transformation matrix and the kinect's pose transformation matrix. Finally, the optimal pose transformation matrix is employed to accomplish the local 3D map and construct the global 3D indoor map. To show the superiority of our method, we make some experiments and compare with some other algorithms. Experimental results show that our method has a better superiority.

关键词： Three-dimensional displays Robots Robot sensing systems Two dimensional displays Kalman filters Feature extraction Buildings

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