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International Conference on Systems and Informatics (ICSAI)

作者： Hui Ren Nan Gao Jia Li Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology School of Information and Telecommunication Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China

ISBN: (数字)9781728152561

ISBN: (纸本)9781728152578

Monocular depth estimation is to perform pixel-level depth estimation on single perspective image, and the methods based on deep learning have shown superior effect for the challenging task. However, the supervised depth estimation methods need costly ground truth labels, which require professional equipment. To solve this problem, we study the unsupervised monocular depth estimation algorithm combining traditional stereo knowledge. We use the unsupervised network based on the reconstruction method as the baseline, which can be trained without direct supervision from ground truth depths leveraging image synthesis on sequences or multi-views images, so that it can improve the accuracy of prediction results without applying any annotations such as LIDAR depth in KITTI. Experiments results on the publicly database KITTI (Eigen split) have shown the promising effectiveness of the proposed method, and compared with state of the art unsupervised algorithms, it has achieved competitive performance in objective evaluation indicators.

关键词： Estimation Image reconstruction Training Task analysis Prediction algorithms Databases Visualization

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An Adaptive Probability Prediction Routing Scheme in Urban DTNs

An Adaptive Probability Prediction Routing Scheme in Urban D...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Zhan Wen Xianghong Tang Xiaoyan Huang Tingwei Fu Jianwei Liu Wenzao Li School of Communication Engineering Chengdu University of Information Technology China Mobile Packet Core Department AT&T Inc USA School of Control Engineering Chengdu University of Information Technology China Date Center Chengdu Xingshu Reconnaissance Infrastructure Engineering Company China School of Computing Science Simon Fraser University Canada

ISBN: (纸本)9781728125848

Most existing DTN routing algorithms can't show efficient network performance. Prophet is a routing protocol widely used for DTNs. The delivery predictability of active nodes will obviously reduce with the same speed as less active nodes. In this paper, we propose an Adaptive Probability Prediction Routing (APPR) approach, which can dynamically adjust the aging factor based on the active degree of nodes. Leveraging the APPR approach, the delivery predictability of each node can be reduced in different speed if the node does not encounter the other node. Furthermore, when two nodes encounter, the forward decision depends on the distance between each node to the destination node, if the delivery predictabilities of encountered nodes are similar. Compared with the traditional Prophet, simulation results demonstrate the proposed APPR approach can significantly improve successful delivery ratio, reduce overhead ratio and the average latency.

关键词： Probability prediction Adaptive probability Routing algorithm Delay tolerant network Routing algorithms Line of nodes active nodes Ganglia Obstetric Delivery Network routing Self tuning

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control of the chaotic phenomenon in robot path using differential flatness 15

Control of the chaotic phenomenon in robot path using differ...

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15th International Conference on Informatics in control, Automation and Robotics, ICINCO 2018

作者： Nasr, Salah Abadi, Amine Bouallegue, Kais Mekki, Hassen Laboratory of Networked Objects Control and Communication Systems National Engineering School of Sousse University of Sousse Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse Tunisia

ISBN: (纸本)9789897583216

This paper deals with the complex chaotic behavior that can appear in the dynamic trajectory of a mobile robot, when the robot is broken or partly damaged. However, a flatness-based controller is designed to ensure the trajectory planning and tracking. Different mathematical tools have been used such as the flatness control technique and non linear chaotic systems. The simulation results for the kinematic controller are presented to demonstrate the effectiveness of this approach. Copyright © 2018 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved

关键词： Mobile robots

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Chaos engineering and control in mobile robotics applications 15

Chaos engineering and control in mobile robotics application...

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15th International Conference on Informatics in control, Automation and Robotics, ICINCO 2018

作者： Nasr, Salah Abadi, Amine Bouallegue, Kais Mekki, Hassen Networked Objects Control and Communication Systems-Laboratory National Engineering School of Sousse University of Sousse Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse Tunisia

ISBN: (纸本)9789897583216

This article briefly summarizes the theory of chaos and its applications. Firstly, we begin by describing chaos as an aperiodic bounded deterministic motion, which is sensitive to initial states and therefore unpredictable after a certain time. Then, fundamental tools of the chaos theory, used for identifying and quantifying chaotic dynamics, are shared. The paper covers a main numerical approach to identify chaos such as the Lyapunov exponents. Many important applications of chaos in several areas such as chaos in electrical and electronic engineering and chaos applications in robotics have been presented. An analysis of the reviewed publications is presented and a brief survey is reported as well. Copyright © 2018 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved

关键词： Chaos control

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2021年 1185卷 v-vi页

作者： Wu, C.H. Patnaik, Srikanta Popentiu Vlãdicescu, Florin Nakamatsu, Kazumi ShatinNew Territories Hong Kong Department of Computer Science and Engineering Faculty of Engineering and Technology Siksha ‘O’ Anusandhan University BhubaneswarOdisha India Information and Communication Engineering Faculty Automatic Control and Computer Science University of Oradea Oradea Romania School of Human Science and Environment University of Hyogo Himeji Japan

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Artificial intelligence enabled radio propagation for communications - Part I: Channel characterization and antenna-channel optimization

arXiv

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arXiv 2021年

作者： Huang, Chen He, Ruisi Ai, Bo Molisch, Andreas F. Lau, Buon Kiong Haneda, Katsuyuki Liu, Bo Wang, Cheng-Xiang Yang, Mi Oestges, Claude Zhong, Zhangdui The Purple Mountain Laboratories Nanjing211111 China The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China Peng Cheng Laboratory Shenzhen518055 China The Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States The Department of Electrical and Information Technology Lund University Lund22100 Sweden The Department of Radio Science and Engineering Aalto University Aalto00076 Finland The School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Purple Mountain Laboratories Nanjing211111 China The Institute of Information and Communication Technologies Electronics and Applied Mathematics Universite Catholique de Louvain Louvain-la-Neuve 1348 Belgium

To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques. In this two-part paper, we investigate the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. It firstly provides a comprehensive overview of ML for channel characterization and ML-based antenna-channel optimization in this first part, and then it gives a state-of-the-art literature review of channel scenario identification and channel modeling in Part II. Fundamental results and key concepts of ML for communication networks are presented, and widely used ML methods for channel data processing, propagation channel estimation, and characterization are analyzed and compared. A discussion of challenges and future research directions for ML-enabled next generation networks of the topics covered in this part rounds off the paper. © 2021, CC BY-NC-ND.

关键词： Machine learning

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Tongue image segmentation via color decomposition and thresholding

Tongue image segmentation via color decomposition and thresh...

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作者： Li, Zuoyong Yu, Zhaochai Liu, Weixia Xu, Yong Zhang, Daoqiang Cheng, Yong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China The Fujian College's Research Base of Humanities and Social Science for Internet Innovation Research Center Minjiang University Fuzhou350121 China Straits Institute Minjiang University Fuzhou350121 China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen518055 China Department of Computer Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

Tongue image segmentation is a crucial step in developing an automatic tongue diagnosis system. After exploring characteristics of image thresholding in different color spaces, we propose a simple and effective tongue image segmentation method. Specifically, the proposed method first extracts an initial tongue body region by performing image thresholding on the transformed hue component in HSI (Hue, Saturation, and Intensity) color space. Then, one of two image thresholding results on the red component of an original tongue image is adaptively selected to find the gap region between the tongue body root and the upper lip. Finally, the initial tongue body region is refined by removing fake object regions such as the upper lip to obtain final tongue image segmentation result. Experimental results on a tongue image dataset containing 200 subjects demonstrate the effectiveness of the proposed method. © 2018 John Wiley & Sons, Ltd.

关键词： Image segmentation

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Study on LED Color Mixing for Stage Lighting Based on Locus Fitting of Blackbody 3

Study on LED Color Mixing for Stage Lighting Based on Locus ...

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3rd IEEE International Conference on Cloud Computing and Internet of Things, CCIOT 2018

作者： Ren, Hui Li, Shuwei Sun, Rongshu Su, Zhibin School of Information Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing Key Laboratory of Modern Entertainment Technology Beijing100024 China

ISBN: (数字)9781538671412

ISBN: (纸本)9781538671412

Aiming at overcoming the defects of basic lighting color rendering for LED stage lighting, this paper establishes a new mixing light method with RGBW four-color mixing model. Compared with traditional tricolor light mixing model, it uses the mixing light of white as the fourth input, with the three-basic color of red, green and blue to obtain a new mixing method. Then the original coefficients of RGBW are optimized after adjusting the two parameters of relative spectral power distribution and illuminance of mixing light for locus fitting of blackbody. Finally, better color rendering of white light can be acquired. By the MATLAB simulation and field testing, experimental results have shown that the proposed method will achieve ideal LED lighting performance, which is convenient for color management of lighting control system in modern theatre. © 2018 IEEE.

关键词： Light emitting diodes

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Coordinated control method of virtually coupled train formation based on multi agent system 2nd

Coordinated control method of virtually coupled train format...

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2nd International Conference on Smart Vehicular technology, Transportation, communication and Applications, VTCA 2018

作者： Liu, Ling Wang, Ping Zhang, Bo Wei, Wei School of Software and Microelectronics Peking University Beijing102600 China Beijing National Railway Research and Design Institute of Signal and Communication Group Co. Ltd. Beijing100070 China Beijing Engineering Technology Research Center of Operation Control Systems for High Speed Railways Beijing100070 China National Engineering Research Center for Software Engineering Peking University Beijing102600 China Key Laboratory of High Confidence Software Technologies Peking University Beijing102600 China

ISBN: (纸本)9783030045814

As China has become the country with the longest operating mileage and largest construction scale of high-speed railway (HSR) in the world, how to improve the operational excellence and customer satisfaction draws increasing attention. In order to further optimize the allocation of transport resource and improve the transportation efficiency of HSR, a coordinated control method using the idea of virtual coupling (VC) based on multi agent system (MAS) is proposed in this paper firstly. At last, the efficiency and feasibility of proposed model and method are demonstrated using a simulation case, which shows that the coordinated control model based on MAS can not only ensure the safety of operation, but also improve the efficiency of a whole train group. © Springer Nature Switzerland AG 2019.

关键词： Multi agent systems

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A Novel Airplane Detection Algorithm Based on Deep CNN

A Novel Airplane Detection Algorithm Based on Deep CNN

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2018国际计算机前沿大会（原国际青年计算机大会）

作者： Ying Wang Aili Wang Changyu Hu Higher Education Key Lab for Measure and Control Technology and Instrumentations of Heilongjiang Harbin University of Science and Technology Department of Communication Engineering Nanjing University of Aeronautics and Astronautics

Driven by the massive natural scene image and computer's high speed computation ability, deep CNN becomes the mainstream method for completing the computer vision task by the power of feature representation *** object detections based on deep CNN are unable to achieve optimization due to lack of training set of remote sensing images, a novel method based on transfer learning and deep CNN combined with SVM is proposed in this ***, we obtain the deep CNN model AlexNet trained on a large-scale data ***, we truncate the first five convolution layers and get the initial parameters through transfer learning. Then, Deep CNN is used as feature extractor to extract the depth feature for training SVM, and the final remote sensing image airplane detection model is obtained. Experimental results show that the average precision of the proposed algorithm outperforms other traditional algorithms.

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