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IEEE/CVF International Conference on Computer Vision (ICCV)

作者： Zheng, Wenbo Gou, Chao Yan, Lan Wang, Fei-Yue Xi An Jiao Tong Univ Sch Software Engn Xian Peoples R China Sun Yat Sen Univ Sch Intelligent Syst Engn Guangzhou Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China

ISBN: (纸本)9781728150239

Since objects in natural scenarios possess various scales and aspect ratios, learning the rich edge information is very critical for vision-based tasks. Conventional generative adversarial networks (GANs) based methods for edge detection don't perform so well due to model collapse. In order to capture rich edge information and avoid model collapse as much as possible, we consider the learning of GANs as an evolutionary optimization and propose a novel method termed as differential-evolution-based generative adversarial networks (DEGAN) for richer edge detection. In particular, built upon GANs structure, we introduce an improved differential evolutionary algorithm to refine the input of generator, with fitness function evaluated by the discriminator. Experimental results on the well-known BSDS500 and NYUD benchmarks indicate our proposed DEGAN can achieve state-of-the-art performance while retaining a fast speed and validate its simplicity, effectiveness, and efficiency. The high quality of our results on edge detection with proposed DEGAN may promise to make other vision-based tasks work better.

关键词： Differential evolutionary algorithm Edge detection Generative adversarial network

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The Smart Street Lighting System Based on NB-IoT

The Smart Street Lighting System Based on NB-IoT

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Chinese Automation Congress (CAC)

作者： Chen, Shichao Xiong, Gang Xu, Jia Han, Shuangshuang Wang, Fei-Yue Wang, Kun Macau Univ Sci & Technol Inst Automat State Key Lab Management & Control Complex Syst Chinese Acad Sci Taipa Macau Peoples R China Chinese Acad Sci Cloud Comp Ctr Dongguan Peoples R China Beijing Univ Chem Technol Inst Automat State Key Lab Management & Control Complex Syst Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol Beijing Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Qingdao Acad Intelligent Ind Qingdao Peoples R China Beijing Univ Chem Technol Beijing Peoples R China

ISBN: (纸本)9781728113128

With the development of communication technology, in order to meet the smart city's demand for intelligent infrastructure, the smart street lighting system based on NB-IoT is an effective method to realize the goal. This paper elab.rates on the smart street lighting system's architecture, including the perception and control layer, the transport layer, the platform layer and the application layer. In addition, the actual system is built to verify. This system uses STM32 to build the perception and controller, and relies on China Telecom's NB-IoT communication network for the data transmission, finally using the IoT management platform-Huawei OceanConnect- to implement the connection management, the device management, the data calculation and the remote control functions. This system verifies the feasibility of the smart street lighting system based on NB-IoT technology, which provides the reference for the promotion and application. It is expected to provide intelligent, diversified, efficient and economical services for the smart cities.

关键词： smart street lighting system NB-IoT IoT smart city

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Type-2 Fuzzy Comprehension Evaluation for Tourist Attractive Competency

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2019年第1期6卷 96-102页

作者： Mo, Hong Yan, Kefu Zhao, Xuanming Zeng, Yaqiong Wang, Xiao Wang, Fei-Yue Changsha Univ Sci & Technol Coll Elect & Informat Engn Changsha 410205 Hunan Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100864 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Changsha 410073 Hunan Peoples R China Univ Chinese Acad Sci Ctr China Econ & Social Secur Beijing 100049 Peoples R China

In general, the evaluation for tourist attractive competency is always by means of natural language, owing to the difficulty for people to use conventional mathematics method to describe the evaluation modeling and their evaluation results. In this paper, discrete and partially connected type-2 fuzzy sets, fuzzy comprehension evaluation, are synthesized, and then discrete type-2 fuzzy comprehension valuation and partially connected type-2 fuzzy comprehension evaluation are presented to provide the analysis of evaluation and represent the results of different conditions. Finally, the method of evaluation for tourist attractive competency is given, and the results illustrate that the method can describe the otherness of evaluated data.

关键词： Fuzzy sets interval type-2 fuzzy sets (IT2 FSs) T2 FSs tourist attractive competency type-2 fuzzy comprehension evaluation

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Nonlinear Deformation Prediction and Compensation for 3D Printing Based on CAE Neural Networks 15

Nonlinear Deformation Prediction and Compensation for 3D Pri...

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15th IEEE International Conference on Automation Science and Engineering (IEEE CASE)

作者： Zhao, Meihua Xiong, Gang Shang, Xiuqin Liu, Chang Shen, Zhen Wu, Huaiyu Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 101408 Peoples R China Chinese Acad Sci Cloud Comp Ctr Donggguan 523808 Peoples R China Sichuan Univ Coll Comp Sci Chengdu 610065 Peoples R China Qingdao Acad Intelligent Ind Intelligent Mfg Ctr Qingdao 266113 Peoples R China

ISBN: (纸本)9781728103563

Although 3D printing technology has developed rapidly in recent years, there are many problems to be solved. The accuracy of the objects obtained by 3D printing is low compared with subtractive manufacturing methods. There are many factors that affect the errors, such as the shape of the object, the properties of the material, and parameters in the printing process. We takes Digital Light Processing (DLP) 3D printing as an example in this paper and take the dental crowns as the test category. We use the Convolutional Auto-Encoder (CAE) architecture to make prediction and compensation for the error of the 3D models directly. We use a simulation method to obtain the data, and test on nonlinear deformation. The results show that our network has a good ability to approximate nonlinear deformation.

关键词： Three-dimensional displays Three-dimensional printing Solid modeling Strain Neural networks Predictive models Biological system modeling

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Generative Adversarial Networks for Parallel Transportation systems

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IEEE intelligent TRANSPORTATION systems MAGAZINE 2018年第3期10卷 4-10页

作者： Lv, Yisheng Chen, Yuanyuan Li, Li Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Qingdao Peoples R China Univ Chinese Acad Sci Control Theory & Control Engn Beijing Peoples R China Tsinghua Univ Dept Automat Beijing Peoples R China

Generative Adversarial Networks (GANs) have emerged as a promising and effective mechanism for machine learning due to its recent successful applications. GANs share the same idea of producing, testing, acquiring, and utilizing data as well as knowledge based on artificial systems, computational experiments, and parallel execution of actual and virtual scenarios, as outlined in the theory of parallel transportation. Clearly, the adversarial concept is embedded implicitly or explicitly in both GANs and parallel transportation systems. In this article, we first introduce basics of GANs and parallel transportation systems, and then present an approach of using GANs in parallel transportation systems for traffic data generation, traffic modeling, traffic prediction and traffic control. Our preliminary investigation indicates that GANs have a great potential and provide specific algorithm support for implement n.g parallel transportation systems.

关键词： Generative adversarial networks Computational modeling Machine learning Predictive models Traffic control Integrated circuit modeling

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Multi-robot Path Planning and Trajectory Smoothing

Multi-robot Path Planning and Trajectory Smoothing

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Hub Ali Gang Xiong Huaiyu Wu Bin Hu Zhen Shen Hongxing Bai School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences China Hubei Jointown Technology Co. Ltd Artificial Intelligence Research Institute Wuhan China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

In this paper we consider a problem in task execution for multi-robot trajectory planning with collision avoidance in a shared working environment. Consider two or more robots generating trajectories towards their respective goal positions. The collision may occur if their trajectory coordinates are intersecting at a point or follow the same path segment simultaneously. The central planner is introduced to control robot motion in the collision state and to reduce the complexity of the multi-robot path planning system. The global path for every robot is generated by the $\mathrm{A}^{*}$ algorithm in a grid-based environment. The path has presented a sequence of optimal grid numbers and later transformed into Cartesian coordinates for smooth trajectory generation. The central planner takes an optimal grid sequence for every robot to analyze the collision state according to its cost value. It regenerates the trajectories to minimize the complexity cost value and replaces the previous trajectory based on minimum cost value. In the collision state, the central planner allows one robot at a time to pass along the conflict path segment and hold others in queue at a safety offset distance until the previous robot passes safely. The algorithm has been applied to robots working in a shared environment in complex maps and the simulations is performed with MATlab.to calculate the efficiency of this approach for handling collision states in a multi-robot path planning system.

关键词： Robot kinematics Trajectory Collision avoidance Task analysis Resource management

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A RELATION NETWORK EMBEDDED WITH PRIOR FEATURES FOR FEW-SHOT CARICATURE RECOGNITION

A RELATION NETWORK EMBEDDED WITH PRIOR FEATURES FOR FEW-SHOT...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zheng, Wenbo Yan, Lan Gou, Chao Zhang, Wenwen Wang, Fei-Yue Xi An Jiao Tong Univ Sch Software Engn Xian 710049 Shaanxi Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Shandong Peoples R China

ISBN: (纸本)9781538695524

Caricature is a simple and abstract description of a person using her/his exaggerated characteristics. Due to amplified facial variations in the caricatures and significant differences among caricature and real face modalities, building vision models for recognizing each other between these modalities is an extremely challenging task. In addition, it is not easy to collect abundant samples of real faces and corresponding caricatures for training vision models, which makes the recognition more difficult. In this paper, we propose a novel relation network via meta learning to address the problem of few-shot caricature face recognition. In particular, we present a deep relation network to capture and memorize the relation among different samples. To employ the prior knowledge, we combine learned deep and handcrafted features to form the hybrid-prior representation via joint meta learning. Final recognition is derived from our relation network by learning to compare between the hybrid-prior features of samples. Experimental results on three caricature datasets of Web-Caricature, IIIT-CFW, and Caricature-207 demonstrate that our method performs better than many existing ones for few-shot caricature recognition.

关键词： Caricature Recognition Meta-Learning Few-Shot Learning Prior Feature

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3-D Tracking for Augmented Reality Using Combined Region and Dense Cues in Endoscopic Surgery

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2018年第5期22卷 1540-1551页

作者： Wang, Rong Zhang, Mei Meng, Xiangbing Geng, Zheng Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Shandong Peoples R China

An augmented reality (AR) technique has recently gained its popularity in minimally invasive surgery. Tracking is a crucial step to achieve precise AR. Besides optical tracking in traditional medical AR, visual tracking attracts a lot of attention due to its generality. Moreover, when the target organ's 3-D model can be obtained from preoperative images and under the model rigidity assumption, tracking is then converted into a problem of computing the six-degree-of-freedom pose of the 3-D model. In this paper, we introduce a robust tracking algorithm in our endoscopic AR system, where we combine the benefits of both region and dense cues in a unified framework. Each kind of cues alone may not be adequate for tracking in endoscopic surgery. However, they have complementary characteristics, with region cues being more robust to motion blur and fast motion, and dense cues being more accurate when motion is not large. We also propose an appearance model adaption method and an occlusion processing method to effectively handle occlusions. Experiments on both synthetic dataset and simulated surgical environment show the effectiveness and robustness of our proposed method. This work presents a novel tracking strategy in medical AR applications.

关键词： Augmented reality dense cues endoscopic surgery region cues tracking

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3-D Motion Analysis and Implementation of a Developed Gliding Robotic Dolphin

3-D Motion Analysis and Implementation of a Developed Glidin...

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IEEE International Conference on Robotics and Biomimetics

作者： Jian Wang Zhengxing Wu Jincun Liu Min Tan Junzhi Yu State Key Lab Management and Control for Complex Systems Institute of Automation CAS Beijing China Dept. Mech. Eng. Sci. Peking University Beijing China

This paper investigates the three-dimensional (3-D) maneuverability of a gliding robotic dolphin through analyzing the horizontal and vertical motions. Concretely, in order to improve the performance in the horizontal plane, the gliding robotic dolphin is developed with a rudder installed on its belly, and the 3-D full-state dynamic model is derived briefly. By setting two typical body and/or caudal fin (BCF)-based and three typical median and/or paired fin (MPF)-based turning patterns, the turning performances are revealed and analyzed. With regard to the vertical plane, a novel finite state machine framework is proposed to realize the vertical downward action. Finally, extensive experiments involving the turning and vertical motions are conducted to illustrate and analyze the 3-D maneuverability, which provides valuable guidance for the real-world applications of the gliding robotic dolphin.

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Acoustic Source Tracking in Reverberant Environment Using A Novel PSO Particle Filter Framework

Acoustic Source Tracking in Reverberant Environment Using A ...

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Chinese Automation Congress (CAC)

作者： Yang, Jing Shang, Xiuqin Hu, Bin Shen, Zhen Xiong, Gang Wang, Hui Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing Peoples R China Chinese Acad Sci Cloud Comp Ctr Dongguan Peoples R China

ISBN: (纸本)9781728140940

In this paper, several methods are combined together and applied to a Particle Filter based on Particle Swarm Optimization acoustic source tracking framework in order to solve some problems of sound source tracking. The Time Difference of Arrival (TDOA), which is extracted from the audio signal received by the microphone pair, makes observations. The Langevin Model is used to describe the speaker's motion characteristics. The pseudo-likelihood function is constructed by using the Global Coherence Field (GCF) function to update the particle weight, in order to solve problem of the phenomenon of spurious source due to noise and reverberation. According to the iterative process and particle flight conditions, the inertial weights of the particles are adjusted nonlinearly and dynamically. The concepts of superior flight speed and inferior flight speed are introduced to Particle Swarm Optimization, which helps jump out of local optimum and solves the problem of lack of particle diversity. Thus, the faster tracking of sound source is realized. In the framework, with fewer particles, the robustness of tracking is enhanced and accuracy of tracking is improved. Finally, the effectiveness of this framework for acoustic source tracking is verified through several Monte Carlo simulation experiments.

关键词： Acoustic localization and tracking Particle Filter Particle Swarm Optimization Global Coherence Field

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