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arXiv 2020年

作者： Wu, Yu-Huan Liu, Yun Zhang, Le Gao, Wang Cheng, Ming-Ming TKLNDST College of Computer Science Nankai University Tianjin300350 China ETH Zurich Switzerland School of Information and Communication Engineering University of Electronic Science and Technology of China China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels. To this end, we propose a new pipeline for end-to-end salient instance segmentation (SIS) that predicts a class-agnostic mask for each detected salient instance. To better use the rich feature hierarchies in deep networks and enhance the side predictions, we propose the regularized dense connections, which attentively promote informative features and suppress non-informative ones from all feature pyramids. A novel multi-level RoIAlign based decoder is introduced to adaptively aggregate multi-level features for better mask predictions. Such strategies can be well-encapsulated into the Mask R-CNN pipeline. Extensive experiments on popular benchmarks demonstrate that our design significantly outperforms existing state-of-the-art competitors by 6.3% (58.6% vs. 52.3%) in terms of the AP metric. The code is available at https://***/yuhuan-wu/RDPNet. © 2020, CC BY-NC-ND.

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Composition Harmony Assessment Method Based on Rule of Thirds

Composition Harmony Assessment Method Based on Rule of Third...

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Culture-oriented Science & Technology (ICCST), International Conference on

作者： Aixia Tang Wei Jiang Jingjing Zhang Shuang Wang Yanting Gao School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology Communication University of China School of Computer Science and Cybersecurity Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Composition harmony mainly refers to the various components of the image that are sensed together as a harmonious and unified organism, it plays a key role in the assessment of image aesthetic quality. In this paper, a composition harmony assessment method based on the rule of thirds was proposed. The eye-tracking dataset was used to extract the saliency regions of the image and the composition harmony assessment method was designed by computing how close the centroid of the largest saliency region and the rule of thirds. Moreover, the effectiveness of the assessment method was analyzed by the subjective evaluation experiment results of the composition harmony. The experimental results showed that the composition harmony assessment method proposed in this paper is effective.

关键词： 6G mobile communication Artificial intelligence

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Research on Color Harmony Evaluation Method based on Color Complexity Measure

Research on Color Harmony Evaluation Method based on Color C...

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Culture-oriented Science & Technology (ICCST), International Conference on

作者： Yanting Gao Jingjing Zhang Shuang Wang Yuncong Peng Aixia Tang School of Information and Communication Engineering Communication University of China Beijing China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) School of Computer Science and Cybersecurity Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Color harmony is an important factor affecting the aesthetic feeling of images and plays an important role in visual perception. It can evaluate the feasibility of images by constructing the computational model of human aesthetic thinking. In this paper, a color harmony evaluation method based on color complexity was implemented. Given the classical color harmony model which is suitable for the simple color combination but not suitable for the complex image, and the local feature redundancy caused by grid sampling, an adaptive sampling based on CCM(color complexity measure) was implemented. Then, K-means was adopted to extract local color harmony features. Finally, a model was constructed between local color harmony features and the overall color harmony by SVM. The results show that the method implemented in this paper can represent the color harmony of complex images accurately and effectively.

关键词： Image color analysis Support vector machines Feature extraction Visual perception Wheels Computational modeling Complexity theory

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Reliable Task Offloading for Vehicular Fog Computing under Information Asymmetry and Information Uncertainty

Reliable Task Offloading for Vehicular Fog Computing under I...

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作者： Zhou, Zhenyu Liao, Haijun Zhao, Xiongwen Ai, Bo Guizani, Mohsen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical and Electronic Engineering North China Electric Power University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Department of Computer Science and Engineering Qatar University Doha Qatar

Vehicular fog computing has emerged as a cost-efficient solution for task processing in vehicular networks. However, how to realize effective server recruitment and reliable task offloading under information asymmetry and uncertainty remains a critical challenge. In this paper, we adopt a two-stage task offloading framework to address this challenge. First, we propose a convex-concave-procedure-based contract optimization algorithm for server recruitment, which aims to maximize the expected utility of the operator with asymmetric information. Then, a low-complexity and stable task offloading mechanism is proposed to minimize the total network delay based on the pricing-based matching. Furthermore, we extend the work to the scenario of information uncertainty and develop a matching-learning-based task offloading mechanism, which takes both occurrence awareness and conflict awareness into consideration. Simulation results demonstrate that the proposed algorithm can effectively motivate resource sharing and guarantee bounded deviation from the optimal performance without the global information. © 2019 IEEE.

关键词： Fog computing

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A survey of few shot learning based on intelligent perception

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Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 2020年 41卷

作者： Song, Chuang Zhao, Jiajia Wang, Kang Liang, Xinkai Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China School of Computer and Technique Fudan University Shanghai200433 China

Few-shot learning refers to using only a small amount of supervision information of the target class to train the machine learning model. Due to its practical values, recent advances in few-shot learning by academia and industry have made significant contributions. However, there were few reviews on this issue in China. This paper systematically summarizes and explores the few-shot learning algorithms and the object detection algorithms based on few-shot learning. Firstly, the problem definition of few-shot learning is given, and its connections with other classic machine learning problems are also enumerated. Meanwhile, the theoretical challenges of the problem of few-shot learning are explained. Then, we summarize the image classification based on few-shot learning, and analyze its representative works. Based on this, we focus on the problem of few-shot object detection, especially the problem of zero-shot object detection, and analyze the existing research works in detail. Finally, we look forward to the future development of few-shot learning in terms of problem setting, theoretical research, implementation technology, and application scenarios based on the advantages and disadvantages of the existing methods. It is expected to provide inspirations for the subsequent research works in this field. © 2020, Beihang University Aerospace Knowledge Press. All right reserved.

关键词： Image classification

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Formal analysis of QUIC handshake protocol using ProVerif

Formal analysis of QUIC handshake protocol using ProVerif

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IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Jingjing Zhang Lin Yang Xianming Gao Qiang Wang College of Command and Control Engineering Army Engineering University of PLA Nanjing China National Key Laboratory of Science and Technology on Information System Security Chinese Academy of Military Science Beijing China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781728165509

ISBN: (纸本)9781728165516

This paper presents a formal analysis of the QUIC protocol. This newly proposed protocol is currently under the process of standardization, and it is still unknown whether the proposed protocol provides the claimed security guarantees. To fill this gap, we model the QUIC handshake protocol in the applied pi calculus and perform a comprehensive formal analysis using ProVerif. To the best of our knowledge, this is the first thorough study on the formal analysis of QUIC handshake protocol.

关键词： Security protocol QUIC Formal verification ProVerif formal analysis Formal verification Handshake Protocol pi calculus

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Fractional-order biological system: chaos, multistability and coexisting attractors

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The European Physical Journal Special Topics 2021年第5期231卷 1061-1070页

作者： Debbouche, Nadjette Ouannas, Adel Momani, Shaher Cafagna, Donato Pham, Viet-Thanh Laboratory of Dynamical System and Control University of Larbi Ben M’hidi Oum El Bouaghi Algeria Department of Mathematics and Computer Sciences Larbi Ben M’hidi University Oum El Bouaghi Algeria Nonlinear Dynamics Research Center (NDRC) College of Humanities and Sciences Ajman University Ajman UAE Department of Mathematics Faculty of Science University of Jordan Amman Jordan Department of Innovation Engineering University of Salento Lecce Italy Nonlinear Systems and Applications Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Vietnam

In this paper, the nonlinear dynamics of the biological system modeled by the fractional incommensurate order Van der Pol equations are investigated. The stability of the proposed fractional non-autonomous system is analyzed by varying both the fractional order derivative and system parameters. Moreover, very interesting phenomena such as symmetry, multi-stability and coexistence of attractors are discovered in the considered biological system. Numerical simulations are performed by considering the Caputo fractional derivative and results are reported by means of bifurcation diagrams, computation of the largest Lyapunov exponent, phase portraits in 2D and 3D projections.

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A registration-aided domain adaptation network for 3D Point cloud based place recognition

arXiv

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arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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Hohmann transfer via constrained optimization

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Frontiers of Information Technology & Electronic Engineering 2018年第11期19卷 1444-1458页

作者： Li XIE Yi-qun ZHANG Jun-yan XU State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power UniversityBeijing 102206China Beijing Institute of Electronic Systems Engineering Beijing 100854China

Inspired by the geometric method proposed by Jean-Pierre MAREC, we first consider the Hohmann transfer problem between two coplanar circular orbits as a static nonlinear programming problem with an inequality constraint. By the Kuhn-Tucker theorem and a second-order sufficient condition for minima, we analytically prove the global minimum of the Hohmann transfer. Two sets of feasible solutions are found: one corresponding to the Hohmann transfer is the global minimum and the other is a local minimum. We next formulate the Hohmann transfer problem as boundary value problems, which are solved by the calculus of variations. The two sets of feasible solutions are also found by numerical examples. Via static and dynamic constrained optimizations, the solution to the Hohmann transfer problem is re-discovered, and its global minimum is analytically verified using nonlinear programming.

关键词： Hohmann transfer Nonlinear programming Constrained optimization Calculus of variations

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Improved K-medoids clustering based on gray association rule

Improved K-medoids clustering based on gray association rule

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International Conference on Intelligent Computing, Communication and Devices, ICCD 2017

作者： Gao, Shiying Zhou, Xiaofeng Li, Shuai Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang110016 China School of Computer Science and Engineering Northeastern University Shenyang110000 China

ISBN: (纸本)9789811089435

This paper presents a new K-Medoids clustering algorithm based on gray relational degree. Analyze the gray incidence of each attribute and convert them into the weights of the attributes, and then apply these weights to the distance measure of the cluster;based on this measure, this paper proposed an improved clustering algorithm: Gray-K-Medoids clustering algorithm and applied it to the analysis of the aluminum electrolysis data. The paper introduces the gray relational degree and the basic principle based on the gray relational degree clustering and introduced the improved algorithm in detail. In order to test the effect of improving the algorithm, it was used to the production data of an aluminum plant, and the results show the effectiveness of the algorithm, has a certain promotional value. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Clustering algorithms

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