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检索条件"主题词=filtering algorithms"

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A Multimodal Breast Cancer Diagnosis Approach Based on EfficientNet and Hybrid Feature Selection

A Multimodal Breast Cancer Diagnosis Approach Based on Effic...

引用

Chinese Automation Congress (CAC)

作者： Wenbin Liu Min Zhou Hong Mo Shili Zhao School of Electric & Information Engineering Changsha University of Science & Technology Changsha China School of Automation & Intelligence Beijing Jiaotong University Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Breast cancer ranks among the top causes of mortality in women globally. Traditional breast cancer diagnosis primarily relies on the prior experience of clinicians, which introduces a significant level of subjectivity to the process. Machine learning, as a technique that learns patterns from data and makes predictions, offers a more objective analysis and shows great potential in clinical diagnosis of breast cancer. However, most existing machine learning methods focus on a single modality, which limits the full utilization of data. Additionally, the black-box nature of end-to-end approaches leads to a lack of interpretability, introducing a degree of decision-making risk. Furthermore, irrelevant and redundant features inherent in the data further affect model performance. To address these issues, this paper proposes an innovative Multimodal Breast Cancer Diagnosis (MBCD) method. Specifically, we combine traditional structured feature extraction methods with the advanced EfficientNet model to extract features from ultrasound images and fuse them to improve the accuracy and comprehensiveness of breast cancer clinical diagnosis. To effectively eliminate irrelevant and redundant features and further enhance model performance, we introduce a novel hybrid feature selection method. This method utilizes SHAP feature importance analysis for filter-based feature selection and employs the Artificial Bee Colony (ABC) algorithm for wrapper-based feature selection, effectively improving feature selection efficiency and prediction accuracy. Finally, we use SHAP interpretability analysis to provide a rational explanation of the prediction results. Experimental results demonstrate that our method offers significant advantages in the clinical diagnosis of breast cancer.

关键词： Accuracy Ultrasonic imaging Fuses Decision making Mortality Machine learning filtering algorithms Feature extraction Breast cancer Clinical diagnosis

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Privacy-aware Hydra (PA-Hydra) for 3D Scene Graph Construction

Privacy-aware Hydra (PA-Hydra) for 3D Scene Graph Constructi...

引用

IEEE World Forum on Internet of Things (WF-IoT)

作者： Erdal Akin Kayode S. Adewole Héctor Caltenco Reza Malekian Jan A. Persson Department of Computer Science and Media Technology Malmö University Malmö Sweden Internet of Things and People Centre Malmö University Malmö Sweden Computer Engineering Department Bitlis Eren University Bitlis Turkiye Ericsson Research Ericsson AB Lund Sweden

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

A 3D Scene Graph (3DSG) is a hierarchical 3D representation of a physical environment. Hydra is a promising real-time spatial perception framework for 3DSG developed by MIT Spark Lab. It uses sensor and camera data from an agent to construct a graph of the environment with five layers and continuously updates it. Albeit its utility and efficiency in generating and updating real-time 3DSG using visual-inertial sensors, Hydra and many other 3DSG frameworks ignore violating to identify private sensitive objects by segmenting, identifying, and reconstructing everything in data. Therefore, in this paper, we enhance Hydra to preserve sensitive data and increase the privacy-awareness of the framework. Accordingly, we propose a Privacy-aware Hydra (Pa-Hydra) framework, which integrates a state-of-the-art Object Detection (OD) algorithm that utilizes a proposed Filter Algorithm to cover sensitive objects with black boxes and prevent them from being constructed by Hydra. We implemented the framework with two popular OD algorithms with two different pre-trained models: You Only Look Once version 9 (YOLOv9) and Real-time Detection Transformer (RTDETR). We evaluated the algorithms using the COCO2017 validation dataset and observed the efficiency of the proposed framework on the uHuman2 (uH2) dataset.

关键词： YOLO Three-dimensional displays Closed box filtering algorithms Transformers Cameras Real-time systems Object recognition Sparks Internet of Things

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Image registration method of Large Volume Parenteral based on improved ORB algorithm

Image registration method of Large Volume Parenteral based o...

引用

Computer Vision, Image and Deep Learning (CVIDL), International Conference on

作者： Jianing Tang Hao Sun Dongyao Jia Zihao He School of Automation and Intelligence Beijing Jiaotong University BJTU Beijing China

ISBN: (数字)9798350373820

ISBN: (纸本)9798350373837

Aiming at the problem of vibration interference caused by mechanical vibration in the intelligent detection of Large Volume Parenteral, this paper studies an improved image registration algorithm that based on the ORB algorithm to compensate for the image position deviation. Firstly, the median filtering method based on extreme value detection is used to remove the interference of random noise; then the image enhancement link based on the Laplacian operator is added for the improvement of the characteristics of dark images; and the Brief descriptor is improved in the feature point description stage, using The $3 \times 3$ neighborhood sampling method is used to replace the original single-point sampling method to avoid noise point interference; finally, the block matching strategy is introduced in the feature point matching stage to improve the matching efficiency. The experimental comparison shows that the improved registration algorithm has better registration effect while maintaining the fastness.

关键词： Vibrations Image registration Matched filters Laplace equations Noise Interference filtering algorithms

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BEVSORT: Bird Eye View LiDAR Multi Object Tracking

BEVSORT: Bird Eye View LiDAR Multi Object Tracking

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Mediterranean Electrotechnical Conference (MELECON)

作者： Loay Alfeqy Hossam E. Abd El Munim Shady A. Maged Diaa Mohamed Mechatronics Engineering Ain Shams University Cairo Egypt Computer and Systems Engineering Ain Shams University Cairo Egypt

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

Multi-object tracking (MOT) is an essential task for robotic solutions, requiring 3D information about objects. Cameras can provide some 3D information, but LiDAR sensors can provide more accurate and reliable 3D data. Recent deep learning tracking techniques have achieved top performance on public datasets; however, they are too complex for edge devices. Filter-based tracking techniques are mature and still used in embedded robotics and automotive applications, but they need to be adapted to handle more complex scenarios. This work adopts Kalman filter-based trackers, proposing a new SORT variant for tracking objects in point cloud addressing the limitations of linear motion assumptions and varying the tracked states to adapt objects in bird eye view perspective.

关键词： Three-dimensional displays Laser radar Tracking filtering algorithms Benchmark testing Birds Data models

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Combined Control System for a Multi-Mode Non-Stationary Plant with a State Delay

Combined Control System for a Multi-Mode Non-Stationary Plan...

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International Russian Automation Conference (RusAutoCon)

作者： S. A. Zhigalova E. A. Shelenok Amur State University Blagoveshchensk Russia Pacific National University Khabarovsk Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The work examines the problem of combined control for a multi-mode non-stationary plant with structural- parametric uncertainty, state delay, operating under the constant action of an external disturbance. To solve it, it is proposed to perform a structural synthesis of the control system based on V. M. Popov's hyperstability criterion and L-dissipativity conditions, also using two correcting devices - a corrector filter and an implicit reference model. In addition, using a genetic optimization algorithm, the parameters of the synthesized combined controller are determined based on a generalized quality criterion. Using the Matlab development environment and its Simulink package, a computational experiment is conducted that demonstrates the quality of operation of the developed control system.

关键词： Performance evaluation Uncertainty Software packages Optimal control filtering algorithms Genetics Mathematical models Delays Optimization Matlab

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Enhanced Compensation Strategy of Inverter Nonlinearity Effect for Permanent Magnet Synchronous Motor Drives

Enhanced Compensation Strategy of Inverter Nonlinearity Effe...

引用

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Qiyao Li Gaolin Wang Zhian Ye Oiwei Wang Guoqiang Zhang Dawei Ding Dianguo Xu School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Department of Electrical and Electronic Engineering Imperial College London London UK

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

The compensation of inverter nonlinearity is of great significance for improving the control performance of permanent magnet synchronous motor drive systems. In this article, an online inverter nonlinearity compensation method based on the adaptive gain second order generalized integral is proposed for obtaining dq-axis current harmonics caused by inverter nonlinearity. Therefore, the complex offline test of the inverter nonlinearity can be avoided. In addition, considering the phase shift of the second order generalized integral filter and the time delay caused by controllers, a suppression strategy based on self-adjustment a bandwidth method is proposed. Finally, the method is verified on an 11.7kW permanent magnet motor test platform.

关键词： Magnetic separation Delay effects Bandwidth filtering algorithms Permanent magnet motors Harmonic analysis Inverters

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State of Charge Estimation for Lithium-Ion Batteries in Hybrid Vessels Using Kalman Filters

State of Charge Estimation for Lithium-Ion Batteries in Hybr...

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International Middle-East Power System Conference, MEPCON

作者： Mahmoud Elsanhoury Janne Koljonen Mohammed Elmusrati Seppo Niemi Digital Economy Platform University of Vaasa Vaasa Finland Automation Technology University of Vaasa Vaasa Finland Telecommunications Engineering University of Vaasa Vaasa Finland Energy Technology University of Vaasa Vaasa Finland

ISBN: (数字)9798350379648

ISBN: (纸本)9798350379655

Lithium-ion (Li-ion) batteries have gained significant attention in applications such as electric vehicles and hybrid vehicles and vessels. An important variable of the battery pack is the state-of-charge (SoC), which is not deterministic and cannot be measured accurately using the currently available methods, but it requires estimation. The Kalman filter algorithm has proven to be reliable in estimating the charging level of Li-ion batteries. In this paper, we compare the performance of two different Kalman-based algorithms in terms of robustness and accuracy, also distinct in the nonlinearity scheme. A polynomial curve fitting method is customized to estimate the essential Li-ion battery parameters based on its Thevenin equivalent circuit model. Then, the output of these parameter estimations is propagated through two Kalman filters: extended Kalman filter (EKF) and the unscented Kalman filter (UKF). The implemented filter algorithms are validated using realistic data collected from a functional hybrid vessel operating between the Nordic countries. Further validation for the battery parameters is done using laboratory experiments on battery packs. The SoC estimation results show that both filters EKF and UKF converge robustly and reliably. However, UKF is further recommended as it outperforms EKF in terms of battery SoC estimation accuracy with an advantage of 0.05% error, hence, making UKF more suitable for real-time Li-ion battery-based applications.

关键词： Lithium-ion batteries Accuracy Fluctuations Estimation filtering algorithms Real-time systems Power system reliability Kalman filters State of charge Monitoring

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Study on Transfer Alignment Method for Nonlinear Filtered Inertial Navigation System

Study on Transfer Alignment Method for Nonlinear Filtered In...

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Aerospace Engineering and Systems (ISAES), International Symposium on

作者： Hui Kang Chunlan Jiang Ming Li Liang Mao School of Mechanical and Electrical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9798350350418

ISBN: (纸本)9798350350425

Aiming at the feature that the transfer alignment of inertial navigation system moving base is a nonlinear system in practical engineering, this paper establishes an accurate nonlinear filtering model for the transfer alignment of moving base by adopting the second-order Markov process to represent the dynamic deflection deformation in the process of transfer alignment and by applying the nonlinear filtering method to the process of transfer alignment of inertial navigation system. Finally, through the simulation comparison with the Kalman filtering method, the results show that the nonlinear filtering algorithm has obvious advantages in the alignment accuracy in the transfer alignment process of the inertial navigation system.

关键词： Accuracy filtering Simulation Inertial navigation filtering algorithms Markov processes Nonlinear dynamical systems Kalman filters Vehicle dynamics Remote sensing

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Noise Reduction of pH Signal Based on Variable Step Size LMS Algorithm

Noise Reduction of pH Signal Based on Variable Step Size LMS...

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International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Han Wang School of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Aiming at the noise reduction problem of pH time series in complex industrial environments, the ideas of normalization and feedback control are introduced to propose an adaptive filtering algorithm based on variable step size LMS (Least Mean Square) algorithm. The algorithm is firstly normalized to cancel signal noise gradient amplification problem and enhance the noise resistance of the system; secondly, the idea of variable step size factor is employed to establish a relationship between the coefficients of the step size and the error signals through the sigmoid function, which improves the stability of the LMS algorithm and the convergence speed. Simulation experiments and industrial field pH data indicate that the algorithm's signal-to-noise ratio has been enhanced by 51.811%, the mean-square error is 0.00285. Compared with the traditional LMS algorithm, wavelet noise reduction algorithm, SG noise reduction algorithm, its signal-to-noise ratio has improved by 40.295%, 21.691%, 30.498%; the mean-square error is reduced by 0.00613, 0.00191, 0.00314, the noise reduction effect is significantly improved, and when compared to the original algorithm, it demonstrates superior performance in both convergence speed and steady-state error.

关键词： Resistance Noise reduction Time series analysis Mean square error methods filtering algorithms Stability analysis Steady-state Numerical stability Signal to noise ratio Convergence

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Research on proxy-based sliding mode controller of super-twisting algorithm

Research on proxy-based sliding mode controller of super-twi...

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IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)

作者： Mengke Qi Rongzheng Wang Qingqing Li Shanhai Jin College of Computer Science and Technology Yanbian University Jilin China

ISBN: (数字)9798350316537

ISBN: (纸本)9798350316544

In order to solve the problem that the proxy-based sliding mode controller can only converge exponentially, resulting in errors. In this paper, we propose a study of a proxy-based sliding mode controller that will use the super-twisting algorithm to improve the original sliding mode controller so that when the input value is constant, the output can converge to the input in the optimal time, thus eliminating the steady state error. And a sliding mode filter is used to avoid the overshooting problem. And the proxy-based sliding mode controller based on super-twisting algorithm is simulated and verified to prove its superiority under closed-loop conditions.

关键词： Automation filtering algorithms Information filters Steady-state Information management Convergence

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