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检索条件"主题词=Filtering algorithms"

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Improved Canny Edge Detection Algorithm

Improved Canny Edge Detection Algorithm

引用

International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign)

作者： Hongpeng Zhang Chang Liu Liangjie Feng Yang Yu School of Sciences Shanghai Institute of Technology Shanghai China

ISBN: (数字)9798350363043

ISBN: (纸本)9798350363050

This paper introduces an improved Canny edge detection algorithm. The algorithm replaces traditional Gaussian filtering with bilateral filtering, which better preserves edge structures and ensures more precise edge detection in detailed regions. Additionally, the algorithm employs adaptive histogram equalization to enhance the local contrast of the image. At the same time, the adaptive thresholding in the algorithm enhances the detection performance for edges of varying intensities, such as weak and strong edges, particularly in low-contrast areas. During non-maximum suppression, a neighborhood comparison of edge pixels is manually implemented based on gradient direction to ensure that only local maximum edges are retained, increasing the precision in processing gradient directions, particularly for slanted or subtle edges. Finally, the algorithm applies morphological techniques to refine edges. Experimental findings show that the enhanced algorithm boosts the accuracy of object edge detection from 0.717 to 0.750.

关键词： Histograms Accuracy filtering Image edge detection Heuristic algorithms Adaptive equalizers filtering algorithms Feature extraction Informatics Morphological operations

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Dynamic Target Sensing for ISAC Systems in Clutter Environment

Dynamic Target Sensing for ISAC Systems in Clutter Environme...

引用

IEEE Conference on Wireless Communications and Networking

作者： Yucong Wang Hongliang Luo Feifei Gao Jianwei Zhao Huihui Wu Shaodan Ma Department of Automation BNRist Tsinghua University Beijing China College of Nuclear Engineering High-Tech Institute of Xi'an Xi'an China Department of Electrical and Computer Engineering University of Macau Macao S.A.R. China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

In this paper, we propose a practical integrated sensing and communications (ISAC) framework to sense dynamic targets from clutter environment while ensuring users communications quality. We design multiple communications beams that can communicate with users while one rotating sensing beam can scan entire space, and then we propose the supporting beam-forming design and power allocation strategies for such design. Unlike most existing ISAC studies that ignore the interference of static environmental clutter on target sensing, we construct a mixed sensing channel that includes both static environment and dynamic targets. When base station receives echo signals, we first provide a practical clutter filtering method to filter out static environmental clutter. Then dynamic target detection and angle estimation are realized through angle-Doppler spectrum estimation (ADSE) and joint detection over multiple subcarriers (MSJD), while distance and velocity estimation are realized through the extended subspace algorithm. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

关键词： Base stations filtering Heuristic algorithms Simulation Estimation Object detection filtering algorithms

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Long and Short-Term User Intent Learning for Sequence Recommendation

Long and Short-Term User Intent Learning for Sequence Recomm...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Zhiwei Zhang Fuzhen Sun Pengcheng Li Wenxuan Zhang Shaoqing Wang Tianhui Wu School of Computer Shandong University of Technology Zibo China Information Center(Emergency Services Center) Beijing Earthquake Agency Beijing China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Personalized recommendation algorithms accurately mine users’ potential intentions by analyzing historical interaction data, deepening the user-item relationship and screening to filter complex information while effectively improving users’ experience and engagement. However, it is difficult to distinguish between embedded features and interaction relationships, and there is still the problem of lack of timeliness in intent representation. Aiming at the above problems, this paper proposes a sequence recommendation model that integrates users’ long and short-term intentions, which models users’ long and short-term intentions as potential factors over time at the fine-grained intention level of interaction, which accurately locates the users’ real intentions at a certain time. Firstly, a dual-layer gated recurrent network is designed to solve the sequential dependency problem in long-term sequences and to capture the changes in the user’s long-term intention through an intent evolution unit based on the attention mechanism. Secondly, an online meta-learning update strategy is optimized for real-time modeling of short-term intentions to take into account current temporal information and content relevance. Finally, the two types of intentions are adaptively fused to predict the interaction probability at the next time. Extensive experiments on three real-world datasets show that the LSI-Rec model significantly outperforms all baseline models on the recommendation task.

关键词： Metalearning Adaptation models Attention mechanisms Neural networks Logic gates filtering algorithms Information filters

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Algorithm research for stochastic dual control based on set member estimation

Algorithm research for stochastic dual control based on set ...

引用

Computer and Information Processing Technology (ISCIPT), International Symposium on

作者： Xiaoyan Zhang Yuxuan Xie Ziyan Shang Jiaoru Huang Suping Zhao Xiaohua Song School of Electronic Information Engineering Xi’an Technological University Xi’an China

ISBN: (数字)9798350388404

ISBN: (纸本)9798350388411

An ellipsoidal state bounding based set member estimation dual control method algorithm is proposed for the control problem under unknown but bounded noise. The algorithm designs a weighting factor in the time updating and the measurement updating phases of the setter estimation, respectively. The weighting parameter for the recursive phase of the measurement update is obtained by minimizing the upper bound of the Lyapunov function of the estimation error; a feedback control strategy is also incorporated to make the system operate towards the desired goal. The final results show that the designed controller ensures effective filtering of unknown but bounded noise and enables the system to achieve optimal control. Simulation studies further validate the effectiveness of the proposed method.

关键词： Weight measurement Uncertainty Upper bound Noise Measurement uncertainty Optimal control filtering algorithms

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Design and Experimental Verification of Microwave Imaging for Bone Fracuture Detection

Design and Experimental Verification of Microwave Imaging fo...

引用

IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Ye Tian Hao Deng Beier Luo Hongli Peng State Key Laboratory of Radio Frequency Heterogeneous Integration Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331520717

ISBN: (纸本)9798331520724

This paper proposes a design of microwave imaging (MWI) for bone fracture detection (BFD). The design comprises a single Vivaldi antenna, which scans linearing along the cross-section of the bone in the frequency range from 8.3 GHz to 11.1 GHz, and the image is reconstructed using a range migration algorithm (RMA) combined with mean filtering algorithm (MFA), which removes the artifacts due to the non-uniform constructure of the bone. A set of simulations and experiments were performed on an ex-vivo animal bone. Results show that the design an detect and locate the bone fracture of 1 mm thickness.

关键词： Microwave antennas Radio frequency Animals Conferences Vivaldi antennas filtering algorithms Bones Microwave filters Image reconstruction Microwave imaging

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Unravelling the Mysteries of Lung Cancer: Harnessing the Power of Deep Learning for Detection and Classification

Unravelling the Mysteries of Lung Cancer: Harnessing the Pow...

引用

Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI), International Conference on

作者： M Dhayalini B. Revathi Alias Ponmozhi Electronics and Communication Engineering SET Dhanalakshmi Srinivasan University Trichy India

ISBN: (数字)9798350354539

ISBN: (纸本)9798350354546

Lung cancer is the leading cause of cancer- related death worldwide. Identifying lung nodules is essential in the early detection of lung cancer, which can progress to tumors. Computed tomography (CT) can help with the diagnosis of lung diseases. The primary goal is identifying malignant lung nodules and categorizing lung cancer as benign or malignant. Various image processing, biomarker-based, and machine-automated methods are used to detect lung cancer, but medical practitioners face challenges in achieving accuracy and early diagnosis. This work proposes a novel approach for early and accurate lung cancer diagnosis using the LeNet-5 algorithm. Initially, a median filter is used for preprocessing. Cancerous nodules in lung images were segmented using a hybrid fuzzy with a genetic algorithm (GA). The proposed LeNet-5 is implemented in MATLAB using the dataset obtained by the Lung Image Database Consortium and the Image Database Resource Initiative. Various performance parameters are compared and evaluated with existing algorithms and cutting-edge methods. The experimental outcomes demonstrate that the suggested algorithm has higher classification accuracy (99.2%) than other methods.

关键词： Image segmentation Image databases Computed tomography Lung cancer Lung filtering algorithms Sensitivity and specificity

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An Entropy-Based Feature Selection Algorithm for Curve Detections and Parameterization in Grayscale Images

An Entropy-Based Feature Selection Algorithm for Curve Detec...

引用

Irish Signals and Systems Conference (ISSC)

作者： Tamás Reiter Michael McCann Nathan Henry Computing Department Letterkenny Atlantic Technological University Ireland Queens University Belfast Northern Ireland

ISBN: (数字)9798350352986

ISBN: (纸本)9798350352993

This paper presents a local-global entropy-based algorithm for image edge band localizations. The proposed method computes a series of locally filtered entropy images at variable window sizes and their corresponding global entropy values. Furthermore, the optimal entropy-filtered image is identified by selecting the one with the lowest corresponding global entropy value hypothetically ensuring the lowest potential disorder or variance within the image. Evaluations are conducted comparing the proposed method with the most popular edge detection techniques using a limited set of industrial semiconductor images, demonstrating competitive results. The proposed algorithm is interesting, input parameter free and integrable with other techniques. However, the computational costs may increase significantly depending on the number of local entropy window sizes that need to be processed. Our algorithm can also be extended for future research to incorporate adaptive local window sizes within the image. This algorithm is not designed to compete with state-of-the-art traditional and deep learning-based edge detectors. Instead, it aims to serve as a reliable, manual-tuning-free feature selection method for grayscale images, particularly in scenarios where intricate intensity values contain rich informational content for measurement analyses.

关键词： Location awareness Image edge detection Detectors Manuals Gray-scale filtering algorithms Feature extraction

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A Computationally Efficient Online Algorithm for Tracking Single Moving Source using Geometrically Constrained Independent Vector Analysis

A Computationally Efficient Online Algorithm for Tracking Si...

引用

IEEE Global Conference on Consumer Electronics (GCCE)

作者： Jiahui Hu Tetsuya Ueda Bo He Shoji Makino Graduate School of Information Production and Systems Waseda University Kitakyushu Japan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

This paper discusses Independent Vector Analysis (IVA)-based moving source separation under a source tracking scenario where at most one speaker moves. Previous research proposed a computationally efficient algorithm to update filters for source separation under a situation where only one speaker is moving. To make this algorithm practical, we need to optimize the filters before one speaker starts moving and select which filter corresponds to the moving speaker. Thus, we applied Geometric Constraint (GC) to increase the filter’s convergence speed and select the filter automatically. Compared with research that applies GC all the time, our contribution is to apply GC only when all speakers are fixed, which results in lower computational complexity while maintaining its separation performance for our scenario.

关键词： Filters Source separation Tracking filtering algorithms Vectors Computational efficiency Computational complexity Consumer electronics Convergence

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Iced Power Line Image Enhancement Method Based on Improved Retinex-Homomorphic Filter

Iced Power Line Image Enhancement Method Based on Improved R...

引用

Chinese Automation Congress (CAC)

作者： Shuxin Lu Huijun Liang Gangcheng Long Rui Zhu Hubei Minzu University Enshi China Hubei Bojin Electric Co. Ltd Enshi China Shandong Normal University Jinan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In order to address issues related to complex backgrounds and poor contrast of transmission line icing image, a line icing image enhancement method is proposed in this paper, which based on improved Retinex-homomorphic filtering. To begin with, to address the issues of uneven brightness and unsatisfactory enhancement effect of traditional homomorphic filtering algorithm, a new filtering function is constructed as the filtering function of improved homomorphic filtering, and the image's high-frequency and low-frequency components are individually processed using the filtering function. Then, to address the edge blurring problem of the traditional Retinex algorithm, the Laplace operator is used to sharpen the edge of the image, and the sharpened image is used as the guided image of the guided filter, and then the guided filter is applied to replace the Gaussian low-pass filter in the conventional Retinex algorithm. Finally, the improved homomorphic filtering and the improved Retinex processing results are fused to obtain the final enhanced image. Experimental results indicate that, in comparison to the traditional algorithm, the enhanced algorithm can significantly improve the line icing image, and is superior to the traditional algorithm in terms of objective evaluation index and subjective visual effect.

关键词： Power transmission lines filtering Image edge detection Brightness Low-pass filters filtering algorithms Visual effects Power system reliability Reliability Image enhancement

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Transform-domain Image Enhancement for Underwater Visual SLAM based on Homomorphic Filter

Transform-domain Image Enhancement for Underwater Visual SLA...

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Shuo Zhang Chaoyu Zhang Wei Wang Xinrui Zeng Bin Luo State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China China Nuclear Power Operation Technology Corporation LTD Wuhan China CNNC Engineering Research Center of Nuclear Industry Special Robot Wuhan China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Underwater visual SLAM algorithms play a vital role in autonomously localizing Autonomous Underwater Vehicles (AUV) in challenging underwater environments. The low-light conditions underwater necessitate the use of artificial lighting sources. However, this can lead to issues such as overexposed or underexposed images, resulting in reduced image contrast and information content. This study introduces a transform-domain image enhancement technique aimed at bolstering the resilience of underwater visual simultaneous localization and mapping (SLAM) systems. Specifically, a homomorphic filtering method is implemented to alleviate the impact of low-frequency lighting variations on images, thereby enhancing overall image clarity and bolstering the performance of visual SLAM systems. The efficacy of this filtering approach is validated through experiments conducted on the AQUALOC dataset. Our findings demonstrate that this method enhances the success rate of visual SLAM tracking, thereby enhancing its utility in AUV localization tasks.

关键词： Location awareness Image quality Visualization Autonomous underwater vehicles Simultaneous localization and mapping filtering filtering algorithms Feature extraction Artificial light Image enhancement

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