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arXiv 2018年

作者： Yu, Changqian Wang, Jingbo Peng, Chao Gao, Changxin Yu, Gang Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Key Laboratory of Machine Perception Peking University Megvii Inc.

Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction. To tackle these two problems, we propose a Discriminative Feature Network (DFN), which contains two sub-networks: Smooth Network and Border Network. Specifically, to handle the intra-class inconsistency problem, we specially design a Smooth Network with Channel Attention Block and global average pooling to select the more discriminative features. Furthermore, we propose a Border Network to make the bilateral features of boundary distinguishable with deep semantic boundary supervision. Based on our proposed DFN, we achieve stateof-the-art performance 86.2% mean IOU on PASCAL VOC 2012 and 80.3% mean IOU on Cityscapes dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Center Difference Set Membership Filter by Zonotopes for Nonlinear System

Center Difference Set Membership Filter by Zonotopes for Non...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Rong Cheng Jian Huang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei P.R. China

The paper proposes an improved approach to state estimation for nonlinear discrete-time systems based on zonotopes. To overcome the inherent defect of Taylors formula, a lower-order multi-dimensional extension of Stirling's interpolation formula is used to realize the linearization of nonlinear models. A nonlinear programming method is used to optimize the guaranteed margin of linearization error to obtain a more compact bound estimation, thereby reducing the conservativeness of the algorithm. Simulation results have shown the effectiveness and improved performance of the proposed algorithm.

关键词： State estimation Taylor series Kalman filters Strips Nonlinear systems Interpolation Noise measurement

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Automatic Reading System for Analog Instruments Based on Computer Vision and Inspection Robot for Power Plant

Automatic Reading System for Analog Instruments Based on Com...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Junzhe Wang Jian Huang Rong Cheng Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei P.R. China

In this paper, an automatic reading system for analog instruments has been designed for monitoring in power plants. In a general automatic reading system, there are many limitations to the reading correctness and system robustness such as the high cost for the reason that there is only one instrument could be monitored by a single system, the strict restrict of the camera angle, and being not suitable for instruments with dense scales and so on. We present some solutions to overcome these limitations. Firstly, we combine a mobile inspection robot with an image capture device and the image processing method to cut the cost of the monitoring of analog instruments in power plants. Then, we use Hough transform and perspective transform to correct the geometric distortion of images caused by camera angle. Eventually, we get the result of dense scaled instruments based on polar transform. Experiments show that our system performs quite well, and the reading error is less than the results which obtained from the general automatic reading system.

关键词： Instruments Cameras Inspection Robot kinematics Transforms Monitoring

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Bidirectional LSTM-CRF for biomedical named entity recognition 14

Bidirectional LSTM-CRF for biomedical named entity recogniti...

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14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2018

作者： Yang, Xuemin Gao, Zhihong Li, Yongmin Pan, Chuandi Yang, Ronggen Gong, Lejun Yang, Geng Jiangsu Key Laboratory of Big Data Security Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing210003 China Zhejiang Engineering Research Center of Intelligence Medicine Wenzhou325035 China Faculty Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing211169 China

ISBN: (纸本)9781538680971

Bio-medical entity recognition extracts significant entities, for instance cells, proteins and genes, which is an arduous task in an automatic system that mine knowledge in bioinformatics texts. In this thesis, we utilized a bidirectional long short-term memory (Bi-LSTM) combined with conditional random fields (CRFs) approach to automatically obtain word representation, obliterated the need for a marvelous number of feature engineering tasks. The consequences of this experiment represent the word representation method can effectually acquire potential semantic information. Without relying on any artificial features, the result on the test dataset obtained 76.81 % F-score. Therefore, the proposed method is expected to advance biomedical text mining in bioinformatics entity recognition. © 2018 IEEE.

关键词： Bioinformatics

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Impulsive Multisynchronization of Coupled Multistable Neural Networks with Time-Varying Delay

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IEEE Transactions on Neural Networks and Learning Systems 2017年第7期28卷 1560-1571页

作者： Wang, Yan-Wu Yang, Wu Xiao, Jiang-Wen Zeng, Zhi-Gang School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan430074 China

This paper studies the synchronization problem of coupled delayed multistable neural networks (NNs) with directed topology. To begin with, several sufficient conditions are developed in terms of algebraic inequalities such that every subnetwork has multiple locally exponentially stable periodic orbits or equilibrium points. Then two new concepts named dynamical multisynchronization (DMS) and static multisynchronization (SMS) are introduced to describe the two novel kinds of synchronization manifolds. Using the impulsive control strategy and the Razumikhin-Type technique, some sufficient conditions for both the DMS and the SMS of the controlled coupled delayed multistable NNs with fixed and switching topologies are derived, respectively. Simulation examples are presented to illustrate the effectiveness of the proposed results. © 2012 IEEE.

关键词： Topology

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Dynamic vehicle scheduling based on HTN 36

Dynamic vehicle scheduling based on HTN

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第36届中国控制会议

作者： Yindong Shen Zhongyi Zeng Zhewei Wu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education

ISBN: (纸本)9781538629185

Vehicle scheduling plays a crucial role in public transport bus companies. An efficient schedule can help bus companies reduce operating costs while being an essential guide to daily operations. However, the precompiled schedule is usually hard to be adhered to in practice due to the diversity of traffic and driving conditions. Therefore, dynamic vehicle scheduling becomes an important supplement to the daily operations. In this paper, a dynamic vehicle scheduling approach based on Hierarchical Task Network(HTN) is proposed. In the approach, two dynamic vehicle scheduling strategies are devised according to the practical scheduling philosophy. The first is to reschedule for individual vehicle independently, the objective is to maximize the execution of the precompiled schedule. The second is to reschedule for multiple vehicles simultaneously, which aims to maintain the scheduled headways. The two strategies are achieved in the HTN planning through different task decomposition processes, which are constrained by vehicle resources currently available. To verify the feasibility, this approach is implemented based on the Simple Hierarchical Ordered Planner 2(SHOP2), which is a domainindependent and state-based forward HTN planner. Experimental results show that the approach has good adaptability to solve dynamic vehicle schedule problem, meanwhile, it can be helpful to deal with the abnormal services agilely and hence to increase the service quality of public transit.

关键词： public transit dynamic vehicle scheduling scheduling strategies HTN planning SHOP2

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Heterogeneous belief formation method based on BP neural network

Heterogeneous belief formation method based on BP neural net...

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2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)

作者： Yifan Zhuang Hongwei Wang Xi Chen School of Automation Huazhong University of Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China School of Management Huazhong University of Science and Technology

The BDI model has always been the focus of subject modeling research, which includes three kinds of thinking states of the rational subject: Belief, Desire and Intention. Belief is the cognition of agent to the world;it is a collection of environmental information, other agent information, and its own information that the agent has;and it is also the basis of the agent's thinking activity. Due to differences in the individual's living environment and experience, the formation of heterogeneous beliefs is an important issue in the BDI model study. This article divides individual belief set into two parts: knowledge belief and achievable belief. This article proposes an overall framework for the formation of individual heterogeneity beliefs: First, the individual's knowledge experience is modeled, and the empirical knowledge is structured and quantified into binary propositions;then the BP neural network learn and memory propositions of different combinations to form heterogeneous beliefs. Experiments show that this method can simulate the heterogeneity of individual beliefs caused by the individual's own experience, and can realize the belief generation mechanism of gradual information flow, limited attention and heterogeneous priors.

关键词： agent Heterogeneous belief formation method based on BP neural network

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IMPROVING PERSON RE-IDENTIFICATION BY ADAPTIVE HARD SAMPLE MINING

IMPROVING PERSON RE-IDENTIFICATION BY ADAPTIVE HARD SAMPLE M...

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IEEE International Conference on image processing

作者： Kezhou Chen Yang Chen Chuchu Han Nong Sang Changxin Gao Ruolin Wang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Civil Engineering Wuhan University Wuhan China

The field of person re-identification has made significant advances riding on the wave of deep learning. However, owing to the fact that there are much more easy examples than those meaningful hard examples in dataset, the training tends to stagnate quickly and the model may suffer from over-fitting. Therefore, the hard sample mining method is fateful to optimize the model and improve the learning efficiency. In this paper, an Adaptive Hard Sample Mining algorithm is proposed for training a robust person re-identification model. No need for hand-picking the images in the batch or designing the loss function for both positive and negative pairs, we can briefly calculate the hard level by comparing the prediction result with the true label of the sample. Meanwhile, an adaptive threshold of hard level can make the algorithm not only stay in step with training process harmoniously but also alleviate the under-fitting and over-fitting problem simultaneously. Besides, the designed network to implement the approach has good generalization performance that can be combined with various of existing models readily. Experimental results on Market-1501 and DukeMTMC-reID datasets clearly demonstrate the effectiveness of the proposed algorithm.

关键词： Training Adaptation models Computational modeling Machine learning Robustness Cameras Task analysis

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Event-Triggered Distributed Extended Kalman Filtering with Randomly Occurring Deception Attack: A Variance-Constrained Approach

Event-Triggered Distributed Extended Kalman Filtering with R...

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第37届中国控制会议

作者： Weihao Song Jianan Wang Jiayuan Shan Housheng Su School of Aerospace Engineering Beijing Institute of Technology School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology

In this paper, a distributed extended Kalman filtering algorithm is developed for a class of discrete-time nonlinear systems subject to stochastic disturbances and randomly occurring deception attacks. In order to utilize the limited communication and computation resources efficiently, the event-triggered communication scheme is introduced such that data transmission is executed only when the predefined condition is violated. Furthermore, a set of independent Bernoulli random variables with known statistical properties is defined to characterize the phenomenon of randomly occurring deception attacks. An upper bound for the estimation error covariance considering the event-triggered meachanism and linearization errors is derived via the varianceconstrained approach. The filter gain for each node can be calculated recursively by solving two Raccati-like difference equations to minimize such an upper bound, which is suitable for online application. Finally, an illustrative example is presented to verify the feasibility and effectiveness of the proposed algorithm.

关键词： Distributed filtering Event-triggered scheme Deception attacks Variance constraints

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A nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity

A nonlinear impulsive control system with impulse time windo...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yuming Feng Zitao Wang Xiaoyu Liu Wei Zhang Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

Based on the fact that there always exists error in the impulsive intensity, which leads to the fact that the coefficient is un-fixed, and in the occurrence of the impulses, we propose a new model, which is called nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity. We find sufficient conditions for ensuring its stability by using Lypunov's method. We choose chaotic Lorenz system and Chua's system as numerical examples to show the effectiveness of the results, by employing such method, the systems are controlled.

关键词： Impulsive control system impulse time windows impulsive intensity stability control systems Impulsiveness Pulses Time windows

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