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International Journal of Pattern Recognition and Artificial Intelligence最新文献

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Research on motion recognition based on deep learning algorithm 基于深度学习算法的运动识别研究
Pub Date : 2024-07-12 DOI: 10.1142/s0218001424520220
Wang Xue, Liu Li, Yingxing Zhang
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引用次数: 0
Automatic segmentation model for Parkinson's images based on SA-U2-Net 基于 SA-U2-Net 的帕金森图像自动分割模型
Pub Date : 2024-07-12 DOI: 10.1142/s021800142457009x
Hui Li, Zi-shan Yang, Weimin Qi, Xinchen Yu, Jiaying Wu, Haining Li
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引用次数: 0
Automatic Face Detection of Farm Images Based on an Enhanced Lightweight Deep Learning Model 基于增强型轻量级深度学习模型的农场图像人脸自动检测
Pub Date : 2024-07-12 DOI: 10.1142/s0218001424560093
Xiaoping Huang, Fei Huang, Jiahui Hu, Huanyu Zheng, Mengyi Liu, Zihao Dou, Qing Jiang
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引用次数: 0
A seismic fault recognition method based on region energy algorithm 基于区域能量算法的地震断层识别方法
Pub Date : 2024-07-05 DOI: 10.1142/s0218001424500150
Lei Chen, Yanqing Liang, Guanglei Qi, Ting-Ting Zhang
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引用次数: 0
Configurable Customized Information Extraction and Processing Pipeline 可配置的定制化信息提取和处理管道
Pub Date : 2024-07-05 DOI: 10.1142/s0218001424590122
Seok Kim, Pierce Lai, Dariyan Khan, Kevin Zhao, Brian Le, Alex Luchianov, Margaret Yu, Patrick Wang
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引用次数: 0
Medical X-ray Image Enhancement using Global Contrast-Limited Adaptive Histogram Equalization 利用全局对比度限制自适应直方图均衡增强医用 X 射线图像
Pub Date : 2024-07-05 DOI: 10.1142/s0218001424570106
Sohrab Namazi Nia, Frank Y. Shih
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引用次数: 0
ShNFN: Shepard Neuro-Fuzzy Network for Intrusion Detection in Fog Computing ShNFN:用于雾计算入侵检测的谢泼德神经模糊网络
Pub Date : 2024-07-05 DOI: 10.1142/s0218001424500186
R. Ganeshan, Meesala Sravani, Archana Kalidindi, PG Om Prakash
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引用次数: 0
PCB defect detection based on improved deep learning model 基于改进型深度学习模型的 PCB 缺陷检测
Pub Date : 2024-07-05 DOI: 10.1142/s0218001424540144
Shih-Hsien Tseng, Chi Kuo
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引用次数: 0
Online Multi-Resource Allocation for Network Slicing in 5G with Distributed Algorithms 利用分布式算法实现 5G 网络切片的在线多资源分配
Pub Date : 2024-07-02 DOI: 10.1142/s0218001423590218
Xuebin Tang
With the increasing scale of mobile cellular network applications, 5G mobile network infrastructure provides customizable services to users in the form of network slices. How to effectively allocate existing resources in real dynamic networks with time-varying network utility is a key issue that previous work did not consider. This paper first initializes the multi-resource allocation problem of network slicing in an online manner, where the utility function is set to change over time. Therefore, we propose Metis, an online network slicing resource allocation framework that combines the time-varying nature of the network utility function given bandwidth and processing power constraints with the requirement of virtual network function isolation. The goal is to maximize the cumulative network utility in the long term and specify multiple resource allocation problems by utilizing concave optimization methods. In addition, a distributed algorithm based on the online alternating direction method of multipliers with regret optimization has been developed to achieve optimal resource allocation. Our mathematical analysis proves that Metis can provably converge to the optimal solution and the result of experiments demonstrates a steady state behavior of Metis, which converges in dynamic network settings.
随着移动蜂窝网络应用规模的不断扩大,5G 移动网络基础设施以网络切片的形式为用户提供可定制的服务。如何在网络效用随时间变化的真实动态网络中有效分配现有资源,是以往工作没有考虑的关键问题。本文首先以在线方式初始化了网络切片的多资源分配问题,其中设置了随时间变化的效用函数。因此,我们提出了在线网络切片资源分配框架 Metis,该框架将带宽和处理能力限制下网络效用函数的时变性与虚拟网络功能隔离的要求相结合。其目标是在长期内最大化累积网络效用,并利用凹优化方法指定多个资源分配问题。此外,我们还开发了一种基于在线交替乘数方向法和遗憾优化的分布式算法,以实现最优资源分配。我们的数学分析证明,Metis 可以收敛到最优解,实验结果也证明了 Metis 的稳态行为,在动态网络环境中也能收敛。
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引用次数: 0
Applying machine learning techniques: uncertainty quantification in nonlinear dynamics characters predictions via gated recurrent unit-based reduced-order models 应用机器学习技术:通过基于门控递归单元的降阶模型进行非线性动力学字符预测的不确定性量化
Pub Date : 2024-06-07 DOI: 10.1142/s0218001424510182
Xun Peng, Hao Zhu, Dajun Xu, Wenzhi Hao, Weizong Wang, Guobiao Cai
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引用次数: 0
期刊
International Journal of Pattern Recognition and Artificial Intelligence
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