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检索条件"主题词=Filtering algorithms"

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Performance Comparison of NWDAF-Based Security Analytics Techniques in 5G/B5G Networks

Performance Comparison of NWDAF-Based Security Analytics Tec...

引用

IEEE International Workshop on Computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Apostolis Garos Nikos Alabasis Victoria Katsarou Georgios Gardikis Dimitris Santorinaios Maria Christopoulou R&D Department Space Hellas S.A. Athens Greece Institute of Informatics and Telecommunications NCSR “Demokritos” Athens Greece

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

This paper evaluates the performance of NWDAF-based security analytics techniques in 5G/B5G networks, focusing on anomaly detection for network security incidents. Utilizing a 5G testbed, the study examines both statistical methods (Z-Score, MAD, Hampel Filter) and machine learning techniques (Isolation Forest, LOF, One-Class SVM) for the detection of control-plane and data-plane DoS/DDoS attacks. Results indicate a better performance of statistical methods over ML algorithms in such volume-based attacks and suggest a hybrid approach, combining statistical and ML methods, to enhance anomaly detection and adapt to diverse network conditions for improved 5G security.

关键词： Support vector machines Machine learning algorithms 5G mobile communication Statistical analysis Focusing Machine learning Forestry Network security filtering algorithms Anomaly detection

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Image Fusion Algorithm Based on Frequency Enhancement and Shared Tensor Dictionary Learning

Image Fusion Algorithm Based on Frequency Enhancement and Sh...

引用

Machine Vision, Image Processing and Imaging Technology (MVIPIT), International Conference on

作者： Guoxia Xu Yue He Lizhen Deng Hu Zhu School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9798331543037

ISBN: (纸本)9798331543044

With the rapid advancement of multi-source imaging technology, image fusion has become crucial in image processing. This technique combines data from various modalities to produce rich fused images for deeper analysis. Existing multi-scale methods often overlook intrinsic correlations between image components. To address this, we propose an image fusion algorithm based on frequency enhancement and shared tensor dictionary learning. This approach learns a shared multidimensional tensor dictionary for sparse representation of components across frequencies and employs a frequency compensation guided filter (FCGF) to enhance high and low-frequency information. Experimental results show that our algorithm demonstrates strong generalizability in multimodal medical image fusion and infrared-visible image fusion, generating higher-quality fused images.

关键词： Tensors Dictionaries Correlation Sparse approximation Machine learning Transforms filtering algorithms Information filters Image fusion Biomedical imaging

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Research on Building Crack Detection Method Based on Improved Canny Algorithm

Research on Building Crack Detection Method Based on Improve...

引用

Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Pingyi Dong Heilongjiang Institute of Construction Technology Harbin China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

Aiming at the limitations of traditional Canny operator in removing false edges and protecting edge details in the edge detection process of building crack images, this paper proposes an improved Canny operator and applies it to the edge extraction of building cracks. A hybrid filter and a median filter are cascaded to preprocess the building crack image. At the same time, the subdivision division method is used in the preprocessing stage to segment the image and remove the isolated points, so as to obtain a clearer image. The nonlinear median filter is used to replace the Gaussian filter in the original algorithm. Combined with the maximum interclass variance method and the gradient histogram algorithm, a new high and low threshold is calculated. This method not only effectively preserves the edge details, but also significantly reduces the generation of false edges. Compared with the traditional method, the method proposed in this paper has obvious advantages in extracting the edge of building crack image. The experimental results show that this method can extract clearer and more complete image edges, and the performance of peak signal-to-noise ratio and false edge suppression is also improved to a certain extent.

关键词： Image segmentation Histograms PSNR Image edge detection Buildings Noise Noise reduction filtering algorithms Information filters Protection

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Bayes Optimal Cardinality Filters for Streaming Count Data

Bayes Optimal Cardinality Filters for Streaming Count Data

引用

International Conference on Information Fusion

作者： R. L. Streit Metron 1818 Library St. Suite 600 Reston VA USA

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

A time sequence of counts of the number of sensor detections is the sum of the number of detections of objects and the number of false alarms. We model the count sequence as an insertion-deletion process, and model the time-varying number of objects as a birth-death process. Under these modeling assumptions, we derive the optimal recursive Bayesian posterior distribution for the number of objects conditioned only on the count sequence. The method is potentially applicable in management science to detect changes in demand in decisionindependent observed data streams and in social media to estimate the number of users who abuse hashtags. A maximum a posteriori (MAP) algorithm for estimating the parameters of the birth-death and insertion-deletion processes is presented.

关键词： Filters Social networking (online) filtering algorithms Information filters Approximation algorithms Bayes methods Streams

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Research on Adaptive Signal Optimization Algorithm of Intelligent Decision Support Enterprise Based on Deep Learning

Research on Adaptive Signal Optimization Algorithm of Intell...

引用

Sensors, Electronics and Computer Engineering (ICSECE), IEEE International Conference on

作者： Junyu Yu School of Management Shanghai University Shanghai China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

In order to solve the problems such as low efficiency of cloud manufacturing resource allocation and unreasonable selection of manufacturing services, this project intends to study the resource-oriented cloud manufacturing resource allocation strategy based on user demand. By introducing the methods of data warehouse, online analysis and processing, and data mining, the functional model of ERP data analysis is established. The dual-track mechanism of case base and model base is applied to the process design of model intelligent decision support system (IDSS) and the corresponding algorithm is proposed. A multi-index optimization modeling method for cloud manufacturing based on time-expense-quality-of-service and customer satisfaction was constructed. In this project, Chebyshev filter is combined with second-order vibration to solve the problem of early convergence of particle swarm. The variation factor is added to the subjective weight to reflect the contrast strength of the target data. The numerical simulation shows that the new algorithm has a wide range of solutions and good convergence performance, and also proves the correctness of the proposed theory and decision method.

关键词： Vibrations Optimization methods filtering algorithms Chebyshev approximation Approximation algorithms filtering theory Manufacturing Sensors Resource management Convergence

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Design and Delay Compensation of Digital Active EMI Filter Based on Adaptive Notch LMS Algorithm

Design and Delay Compensation of Digital Active EMI Filter B...

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Energy Storage and Conversion (ISESC), CPSS & IEEE International Symposium on

作者： Zilu Zhang Xuejun Pei Qichi Chen Chunyu Yang Peng Zhou Guifeng Geng Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China China Ship Development and Design Centre Wuhan China

ISBN: (数字)9798350380514

ISBN: (纸本)9798350380521

As power electronics move to high switching frequency, electromagnetic interference (EMI) is receiving increasing attention. The application of digital active EMI filters (DAEF) effectively reduces the size of passive filters and improves the applicability of AEF. However, the characteristics of noise sources change with the changing working conditions, which requires greater adaptability. Therefore, this paper designs an adaptive DAEF based on the LMS algorithm. A delay compensation algorithm is also proposed to address the delay issue introduced by the system's secondary path.

关键词： Employee welfare Passive filters Switching frequency Electromagnetic interference Noise filtering algorithms Power electronics Hardware Delays Energy storage

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Smart Phone-Assisted Rapid Aggregate Size Analysis Technology

Smart Phone-Assisted Rapid Aggregate Size Analysis Technolog...

引用

International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Yiran Wang Jun Wei Kai Zhu Wenlong Zhou Jinming Chen Jiguang Han School of Automation and Electrical Engineering University of Jinan Jinan China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

Particle size distribution or aggregate gradation is the key to ensure the quality of concrete and optimize the structure design. In this paper, a method of measuring aggregate particle size distribution based on smartphone image is proposed. Firstly, the image contrast is enhanced by gray-scale and luminance transform, and the noise is removed by adaptive median filtering algorithm, and the edge of particles is preserved. Then the watershed algorithm is used to segment the image on the basis of clustering, and the two-dimensional shape and size parameters are extracted from the segmentation results. Compared with the screening method and the manual measurement method, the cumulative error rate of this method is controlled within 5%, which verifies its reliability. This method is suitable for rapid assessment of aggregate particle size distribution and provides effective technical support for quality control of concrete engineering.

关键词： Image segmentation Atmospheric measurements Aggregates Signal processing algorithms Clustering algorithms Manuals Biomedical measurement filtering algorithms Size measurement Particle measurements

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Application of Comprehensive State Adaptive Vector Filter Algorithm in Vehicle Navigation

Application of Comprehensive State Adaptive Vector Filter Al...

引用

Control Theory and Applications (ICoCTA), International Conference on

作者： Zhikuan Hou Shuai Chen Haifeng Li Chao Xue Chuan Xu School of Automation Nanjing University of Science and Technology Nanjing China Kunming Campus Army Academy of Border and Coastal Defence Yunnan China

ISBN: (数字)9798331506155

ISBN: (纸本)9798331506162

Currently, navigation technology is transitioning from SINS/GNSS integrated systems to multi-source information fusion. Faced with complex and ever-changing working conditions, some sensors may experience performance degradation, leading to system performance fluctuations and an inability to continuously output accurate navigation information. To address this issue, this paper proposes a combined navigation scheme consisting of SINS/GPS/odometer/ barometer /magnetometer. This information fusion algorithm is based on the federated Kalman filter (FKF) architecture and innovatively introduces the vector allocation factor algorithm, proposing a Comprehensive State Adaptive Vector Filter algorithm (CSAVF). At the subsystem level, calculate the F-norm of the covariance matrix, obtain the dynamic allocation factor, and then extract the singular values of the observable matrices of each system to obtain the allocation factors of each state variable. By incorporating the above factors into the fusion framework, the adaptive performance of the system can be improved. Finally, an unmanned ground vehicle navigation experimental platform was built, and semi-physical simulation experiments and real-time sports car tests were conducted. The experimental results show that the designed multi-source fusion navigation system has high adaptive performance, can effectively reduce the negative impact of partial sensor performance degradation on the integrated navigation system, and has high engineering application value.

关键词： Fault tolerance Navigation Heuristic algorithms Software algorithms Fault tolerant systems filtering algorithms Dynamic scheduling Vectors Resource management Vehicle dynamics

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A Target Detection Algorithm Suitable for Embedded Devices

A Target Detection Algorithm Suitable for Embedded Devices

引用

Electronics and Communication, Network and Computer Technology (ECNCT), International Conference on

作者： Zhibo Wang Shengjie Zhou School of Intelligent Manufacturing and Electronic Engineering Wenzhou University of Technology Wenzhou China Business School Xiamen Institute of Technology Xiamen China

ISBN: (数字)9798350366143

ISBN: (纸本)9798350366150

Due to the limited memory and computing power of embedded devices, running deep learning based object detection algorithms for real-time parsing on drone platforms poses great challenges. At the same time, the detection accuracy of algorithms needs to be improved in small targets, high-density, and multi category scenarios. Under this premise, a lightweight NCWS-YOLO algorithm was constructed, based on the YOLOv5 algorithm, combined with a non maximum suppression method and a weighted box fusion algorithm. The NCW method was proposed, and the target box screening network at the prediction end was reconstructed. The algorithm was deployed on embedded devices to achieve target detection tasks on unmanned aerial vehicle datasets.

关键词： YOLO Accuracy Embedded systems filtering Clustering algorithms filtering algorithms Prediction algorithms Real-time systems Image reconstruction Drones

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TriDeFusion: Enhanced denoising algorithm for 3D fluorescence microscopy images integrating modified Noise2Noise and Non-local means

TriDeFusion: Enhanced denoising algorithm for 3D fluorescenc...

引用

IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Ivan Zolin Vyacheslav Chukanov Ekaterina Pchitskaya Institute of Physics and Mechanics Institute of Biomedical Systems and Biotechnology Laboratory of Biomedical Imaging and Data Analysis Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Institute of Physics and Mechanics Laboratory of Biomedical Imaging and Data Analysis Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Institute of Biomedical Systems and Biotechnology Laboratory of Biomedical Imaging and Data Analysis Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (数字)9798331532024

ISBN: (纸本)9798331532031

Fluorescence microscopy is a technique for obtaining images of luminous objects of small size. It is widely used in fields ranging from materials science to neurobiology. Fluorescence microscopy has several advantages over other forms of microscopy, offering high sensitivity and specificity. However, it often results in images with noise and distortions, complicating subsequent analysis. This paper introduces the TriDeFusion algorithm for 3D image denoising, integrating Non-Local Means (NLM) and Modified Noise2Noise (N2N) techniques. Our results show that TriDeFusion significantly improves image quality, particularly in preserving details while reducing noise. In experiments with synthetic data, the combined methods outperformed individual approaches in both Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR) metrics, achieving up to a 54% reduction in RMSE and a 20% increase in PSNR. For real data, our algorithm demonstrated a significant reduction of noise mean intensity by over 50% and variance by 33%, confirming its robustness and effectiveness across different noise levels and data types.

关键词： Three-dimensional displays PSNR Microscopy Noise Noise reduction Fluorescence filtering algorithms Sensitivity and specificity Root mean square Synthetic data

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