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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

共 691 条记录，以下是651-660 订阅

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Task Offloading Strategy in Satellite Edge computing Based on Matching Game 23

Task Offloading Strategy in Satellite Edge Computing Based o...

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proceedings of the 2023 12th international conference on Networks, Communication and computing

作者： Hufan Cao Houpeng Wang Tao Wu Zhonglin Guo Suzhi Cao China University of Chinese Academy of Sciences China Beijing Institute of Control and Electronic Technology China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences China

ISBN: (纸本)9798400709265

the Low Earth Orbit (LEO) satellite network, serving as a vital complement to the terrestrial backbone network, has emerged as a prospective path for future mobile communication systems, owing to its extensive coverage. In this paper, a three-tier computing architecture catering for application scenarios where ground terminal has limited resources and elevated quality of service (QoS) requisites is presented. the proposed design features vertical collaboration among ground users, LEO satellites, and remote cloud servers, providing collaborative computing task offloading capabilities. We consider the delay and energy consumption of the system, formulated the offloading decision problem as a nonlinear integer programming problem, and then introduced an offloading mechanism that utilizes an improved version of the Gale-Shapley (GS) algorithm and non-cooperative game theory (MGSCO) to approximate the optimal solution under specified constraints. the outcomes of simulations indicate that this strategy can significantly mitigate system delays and energy consumption, in contrast to reference strategies.

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Deep Reinforcement Learning-Based Computation Offloading for Anti-jamming in Fog computing Networks 22

Deep Reinforcement Learning-Based Computation Offloading for...

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proceedings of the 2022 12th international conference on Communication and Network Security

作者： Yongjie Yang Shanshan Tu Haishuang Yan Yihe Zhang Aiming Wu Xuetao Bai Engineering Research Center of Intelligent Perception and Autonomous Control faculty of Information Technology Beijing University of Technology China China Mobile (Suzhou) Software Technology Co. Ltd. China Mobile (Suzhou) Software Technology Co. Ltd. China

ISBN: (纸本)9781450397520

With the rapid development of IoT and fog computing, mobile devices can offload computing tasks into the fog layer to reduce energy consumption and transmission delay. However, the communication between fog nodes and end users is vulnerable to malicious jamming attacks. In this paper, we propose a reinforcement learning-based computation offloading strategy to choose fog nodes, offloading rate, and transmit power to address jamming attacks and interference problems. We use dueling deep Q-network to accelerate the learning speed in the system, which can effectively determine the offloading strategy. the simulation results show that this scheme based on DDQN is better than DQN and Q-learning in terms of computational latency and energy consumption.

关键词： Dueling deep Q-network Fog computing Computation offloading Anti-jamming

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Key Points Positioning: A Two-Stage Algorithm For Single-view Point Cloud of Human Back Based on Point-wise Network 22

Key Points Positioning: A Two-Stage Algorithm For Single-vie...

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proceedings of the 2022 11th international conference on computing and pattern recognition

作者： Nan Dong Xinfeng Zhang Xiaomin Liu Wei Guo Fei Wang Beijing University of Technology China Air Force Medical Center PLA China

ISBN: (纸本)9781450397056

Point cloud data is a collection of massive points containing the spatial position of each point on the target surface, which contains abundant spatial information. At present, it is also applied to the digital modeling of human surface in medical imaging, as the data basis for subsequent human body measurement, morphology estimation and data analysis. Among them, the key points is defined as the landmark position of the surface morphology analysis, those key points provides a reference position for the analysis work, and also reflects the symmetry of the body to a certain extent and morphology information. Aiming at the back shape analysis in clinical diagnosis, this paper proposes a two-stage key points positioning scheme of coarse segmentation and fine positioning. We design and build an pointwise artificial neural network to roughly locate the body part, in this part, we propose a maximum pooling module based on spatial location coding to express local features more strongly. Farther, we propose a gray distance and curvature based operator to match the position of key points. the experiment, shows that our method can effectively enhance the distinctiveness of features and meanwhile, reduce the influence from background.

关键词： Part Segmentation Deep Learning Point Cloud pattern recognition

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A Lightweight Brain Tumor Segmentation Network Based on 3D Inverted Residual Modules 22

A Lightweight Brain Tumor Segmentation Network Based on 3D I...

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proceedings of the 2022 11th international conference on computing and pattern recognition

作者： Yuchao Liu Xia Du Da-Han Wang Shunzhi Zhu Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology China

ISBN: (纸本)9781450397056

Semantic segmentation technology based on deep learning has played an important role for doctors in identifying brain tumor regions and formulating treatment plans. Popular automated segmentation methods for brain tumors include 2D and 3D convolution networks. the 3D networks give better results but lead to a significant increase in parameters and computational cost. In this paper, we propose a lightweight brain tumor segmentation network composed of 3D inverted residual modules, which can significantly reduce the computational complexity of 3D models. Based on a lightweight depthwise separable convolution, our 3D inverted residual module extracts high-dimensional brain tumor features through an intermediate expansion layer, thus improving performance. On the brain tumor dataset BraTS 2018, our network achieves dice scores of 80.8%, 90.7%, and 84.3% (for ET, WT, and TC, respectively) with only 0.68M parameters and 51.46G FLOPs. the results show that our method can significantly reduce the complexity of the 3D model and achieve very competitive performance.

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A Real-Time Voice Conversion Method Based on A Non-Parallel Corpus for Training 22

A Real-Time Voice Conversion Method Based on A Non-Parallel ...

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proceedings of the 2022 11th international conference on Networks, Communication and computing

作者： Yang Li Tong Nie Yucheng Shao Zesheng Zhu Tian Yang Shengnan Zhang Ze Zhu Fang Zhang High-tech Institute FanGong-ting South Street on the 12th China

ISBN: (纸本)9781450398039

Voice conversion (VC) is a modification of a person's voice to imitate a certain target person. Real-time VC can be widely used in confidential communication, voice enhancement, speech synthesis, and other fields, and has important research value. According to current research, high-quality VC methods tend to be computationally complex, and it is difficult to achieve real-time processing on computing platforms with different performances, which limits the usefulness of these methods. In this study, the authors proposed a VC method that can simplify computation based on different hardware processing capabilities to achieve real-time processing. the method also uses the vowel /a/ for speech feature alignment during training, which is a method with a non-parallel corpus and has stronger practicality. the authors designed and implemented a real-time VC system by using this method. through a series of experiments, it was demonstrated that the system has good VC quality while ensuring real-time processing.

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Verifiable Conditional Broadcast Proxy Re-encryption Based on Certificateless Public Key Scheme 23

Verifiable Conditional Broadcast Proxy Re-encryption Based o...

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proceedings of the 2023 6th international conference on Artificial Intelligence and pattern recognition

作者： Sheping Zhai Xianjing Lu Haonan Nie Rui Yang Department of computing Xi'an University of Posts&Telecommunications China

ISBN: (纸本)9798400707674

Conditional broadcast proxy re-encryption can grant fine-grained authorization to ciphertext based on conditions. Most existing schemes are based on public key infrastructure or identity public keys, which poses issues with certificate management and key escrow. To solve these problems, a conditional broadcast proxy re-encryption scheme based on certificateless Cryptosystem is proposed. When generating the original ciphertext, a commitment value is added, and the data user verifies the security of the message after receiving the ciphertext. At the same time, the proxy server verifies the compliance of the conditions before re-encrypting, ensuring that only ciphertext that matches the conditions can be re-encrypted. the simulation results show that the proposed scheme has high computational efficiency in the process of re-encryption key generation and re-encryption and provides a basis for ciphertext sharing in distributed Cloud storage and other applications.

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Towards Industrial Control from the Edge-Cloud: A Structural Analysis of Adoption Challenges According to Industrial Experts 22

Towards Industrial Control from the Edge-Cloud: A Structural...

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proceedings of the 12th international conference on the Internet of things

作者： Marco Giani Nelly Frank Alexander Verl Robert Bosch GmbH: Corporate Sector Research and Advance Engineering Germany University of Stuttgart: Institute for Control Engineering of Machine Tools and Manufacturing Units Germany

ISBN: (纸本)9781450396653

the migration of industrial controls to an edge-cloud hosted on factory premises can reduce operation costs and increase the interoperability and flexibility of industrial machines. However, the adoption of Industrial Internet of things (IIoT) technologies to realize an industrial edge-cloud for factory automation is likely to lead to a number of challenges that have not yet been investigated. Based on an expert interviews study, this paper provides two main contributions: (1) the identification of 11 technology-, engineering-, organization-, and strategy-related challenges that, according to industrial experts, will hinder the adoption of edge-cloud control (ECC) in future factories, (2) the derivation of a structural model showing how challenges are interlinked. the results illustrate the dependency between profitability and both engineering and operation of an ECC system, suggesting the importance of improving the usability of ECC for automation experts with limited IT know-how, for instance through the reorganization of departments and the standardization of integration concepts for ECC in factories.

关键词： Industrial Automation Cloud computing IIoT Edge computing

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SPoW: A solution to the problem of centralization of computing power 22

SPoW: A solution to the problem of centralization of computi...

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proceedings of the 2022 12th international conference on Communication and Network Security

作者： Xuetao Bai Shanshan Tu Haishuang Yan Yongjie Yang Aiming Wu Yihe Zhang Engineering Research Center of Intelligent Perception and Autonomous Control faculty of Information Technology Beijing University of Technology China China Mobile(SuZhou) Software Technology Co. Ltd China Mobile(SuZhou) Software Technology Co.Ltd China

ISBN: (纸本)9781450397520

As the underlying data structure of encrypted digital currency, blockchain technology has become the key technology of current research because of its decentralization characteristics. Engineers and scholars from industry and academia have also extensively discussed the opportunities that the combination of blockchain technology and traditional industries may bring to the development of the industry. However, the consensus algorithm used by the current blockchain technology has the problem of energy waste caused by the centralization of computing power. In response to this problem, after in-depth research on the mechanism of traditional consensus algorithms and the process of reaching consensus, this paper proposes an SPoW algorithm that separates computation and verification to solve the problem of centralization of computing power. At the same time, in order to ensure decentralization, this paper combines the economic Kznets ratio to measure the degree of decentralization and introduces deep reinforcement learning to dynamically balance the number of node tokens.

关键词： Reinforcement learning Kznets ratio Consensus algorithm Blockchain

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Performance Optimization Blockchain-Enabled Fog computing with Deep Reinforcement Learning 22

Performance Optimization Blockchain-Enabled Fog Computing wi...

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proceedings of the 2022 12th international conference on Communication and Network Security

作者： Yihe Zhang Shanshan Tu Shengju Zhang Yongjie Yang Aiming Wu Xuetao Bai Engineering Research Center of Intelligent Perception and Autonomous Control faculty of Information Technology Beijing University of Technology China China Mobile (Suzhou) Software Technology Co. Ltd China Mobile (Suzhou) Software Technology Co. Ltd China

ISBN: (纸本)9781450397520

With the rapid development of Internet of things technology and cloud computing technology, Fog computing emerges with the demand of distributed and decentralized. Blockchain is considered to be an advanced technology, which enables Fog computing data to be stored and shared safely, greatly improving the security and privacy of Fog computing. However, the Blockchain technology currently applied in Fog computing still has some significant disadvantages, one of which is the low throughput performance. In order to meet the demand of improving throughput, this paper proposes a Blockchain-Enabled Fog computing performance optimization framework based on Deep Reinforcement Learning (DRL), which can dynamically adjust according to the system state to improve throughput. Dueling Deep Reinforcement Learning is adopted to obtain the optimal configuration, which can be dynamically adjusted according to Fog node status, network bandwidth and user's quality of service (QoS) requirements, including dynamic selection of block producers, block size and network bandwidth allocation. Simulation results show that the proposed scheme can effectively improve throughput performance.

关键词： Blockchain quality of service Deep Reinforcement Learning Fog computing

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Computation Offloading in Mobile Edge computing-Enabled Blockchain using Matching and Contract theory 23

Computation Offloading in Mobile Edge Computing-Enabled Bloc...

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proceedings of the 2023 12th international conference on Networks, Communication and computing

作者： Yijun Li Liming Chen Wenjie Zhang Yifeng Zheng Ziqiong Lin School of Computer Sciences Minnan Normal University China Zhangzhou Afffliated Hospital of Fujian Medical University China

ISBN: (纸本)9798400709265

the application of blockchain technology on mobile devices requires significant computing resources. However, the limited capacity of mobile devices cannot meet the high computing power requirements of blockchain technology, which limits the development of blockchain technology. Mobile Edge computing (MEC) is capable of alleviate the limited computing capacity of IoT terminals. this paper introduces an edge computing-enabled blockchain system consisting of an edge computing allocation center (ECAC), multiple edge service providers (ESPs), and multiple miners. To efficiently allocate resources between these miners and ESPs, we propose a hierarchical computation offloading strategy based on contract theory and matching game. During contract design phase, ECAC designs a contribution-reward contract to attract ESPs to join the trading market, and provide services to miners. By analyzing the attributes and conditions of feasible contracts of feasible contract, the optimal contract is devised using Lagrange multiplication. During matching phase, an iterative matching algorithm (IMA) is proposed to achieve the matching between ESPs and miners by constructing preference sets for miners and ESPs. Both the stability and convergence have been proved by theoretical analysis. Finally, we conduct experiments to validate the feasibility and effectiveness of the design contract. Experimental results also demonstrate the stability of IMA matching algorithm.

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