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检索条件"任意字段=6th International Conference on Soft Computing and Signal Processing, ICSCSP 2023"

共 113 条记录，以下是31-40 订阅

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Computer-Aided Detection of Atrial Fibrillation Episodes from Electrocardiogram signals Using Variational Mode Decomposition 6

Computer-Aided Detection of Atrial Fibrillation Episodes fro...

引用

6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Parashar, Deepak Sharma, Kanhaiya Symbiosis Institute of Technology Symbiosis International University Computer Science & Engineering Department Maharashtra Pune India

ISBN: (纸本)9798350304480

Atrial Fibrillation (AF) is defined as a heart beating irregularly. It may increase the risk of stroke and sometimes results in heart failure. Lately, the number of patients with AF episodes has increased exponentially worldwide. Early detection is the only way to reduce and control its effect. However, it is crucial to detect AF in the early stages in most patients who do not show any significant symptoms in the early stage. Many recent studies have shown ways to identify early symptoms based on the signature present in the recording of the electrocardiogram. Usually, the signature is present in terms of either frequency domain or time-frequency domain characteristics. None of the studies have shown classification using features from each domain and described the specific behavior of each feature relating to the characteristic of AF. In this work, a rigorous collection of features from each domain is calculated and analyzed for the automatic detection of AF patterns using variational mode decomposition. High-frequency decomposed components have been used for further processing. the dataset from the MIT-BIH repository has been utilized to measure the robustness of the introduced approach. We obtained the highest accuracy of 98.67% on the MIT-BIH database. Obtained indicators show that the proposed method outperformed latest approaches. © 2023 IEEE.

关键词： Atrial Fibrillation Classification Feature Extraction signal processing Variational Mode Decomposition

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No-Reference Image Quality Assessment Based on Active Reasoning Module 6

No-Reference Image Quality Assessment Based on Active Reason...

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6th IEEE international conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Qi, Junwei Deng, Yuhao Wang, Qingchun Yang, Zhen Li, Yingsong College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Shanghai Yanding Information Technology Co. Ltd. Shanghai201210 China College of Computer Science and Technology Harbin Engineering University Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350399059

We present a no-reference image-quality - assessment algorithm based on active reasoning module. this algorithm has three modules: the feature extraction module, the active reasoning module, and the quality assessment module. the active reasoning module incorporates the generator component of the generative adversarial network and enhances its structure with the Res2Net architecture. By integrating this module into the backbone feature extraction network, we improve the receptive field of each convolutional layer, enabling the network to capture information at different scales of the image. To preserve the texture information of the image, we input the gradient map of the distorted image, the distorted image itself, and the image features generated by the generator into the quality assessment module, which has a multi-feature regression networks. this module establishes a mapping model from image-feature to image-quality scores. We conducted experimental analysis of this algorithm on three widely used public datasets, confirming the excellent performance and superiorities of the presented algorithm. the results validate the effectiveness of the designed algorithm and its ability to assess image quality accurately. © 2023 IEEE.

关键词： Image quality

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A New Adaptive Digital signal processing Algorithm 1

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6th international conference on Innovative computing and Communication, ICICC 2023

作者： Meena, Shiv Ram Rai, Chandra Shekhar University School of Information Communication and Technology Guru Gobind Singh Indraprastha University New Delhi110078 India

ISBN: (数字)9789819930104

ISBN: (纸本)9789819930098

In this paper, a new gradient-based adaptive digital signal processing algorithm is proposed that works on the principle of steepest descent method. A new cost function is synthesized with aim to combine best part of LMS and RLS. the cost function is based on weighted least mean square error. the convergence of the adaptive digital signal processing algorithm is proved mathematically. Proposed algorithm was implemented successfully on noise cancellation to validate the convergence. the proposed weighted least mean square algorithm is easy to implement and fast converging. Performance of the algorithm was compared with least mean square algorithm in noise cancellation and found that proposed algorithm is faster converging. the proposed algorithm converges within 0.1 s, while LMS takes 0.6 s to converge. Further, the proposed algorithm is also implemented for 50 Hz powerline humming noise reduction from ECG signal and found robust performance. If the initial value of filter weights in the proposed algorithm is kept nonzero, then performance is much better. As previous errors contribute to error updating, the filter taps quickly reach their optimum value. the proposed algorithm convergence is validated by simulation results. this algorithm has robust and better performance than least mean square algorithm. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electrocardiograms

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6th EAI international conference on Advanced Hybrid Information processing, ADHIP 2022

6th EAI International Conference on Advanced Hybrid Informat...

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6th EAI international conference on Advanced Hybrid Information processing, ADHIP 2022

ISBN: (纸本)9783031288661

the proceedings contain 109 papers. the special focus in this conference is on Advanced Hybrid Information processing. the topics include: Design of Remote Video Surveillance System Based on Cloud computing;physical Movement Monitoring Method of College Physical Education Students Based on Genetic Algorithm;research on Large Data Mining for Online Education of Mobile Terminal Based on Block Chain Technology;Separation Algorithm of Fixed Wing UAV Positioning signal Based on AI;research on Hybrid Maintenance Cost Prediction of Smart Grid Based on Multi-dimensional Information;infrared Image Face Recognition Method Based on signal Interference Technology;remote Tutoring System of Ideological and Political Course Based on Mobile Client;operational Risk Prevention and Control Monitoring of Smart Financial System Based on Deep Learning;remote Monitoring Method of Athlete Training Intensity Based on Mobile Internet of things;research on Equipment Management System of Smart Hospital Based on Data Visualization;Design of Pond Water Quality Monitoring System Based on Mobile UAV Technology;Design of Information Consultation System for the Whole Process of Construction Engineering Based on BIM Technology;the Mobile Teaching Method of Law Course Based on Wireless Communication Technology;design of Financial and Economic Monitoring System Based on Big Data Clustering;recommendation Method of College English Online Mobile Teaching Resources Based on Big Data Mining Algorithm;Design of Electronic Communication Power Monitoring System Based on GPRS Technology;online Interactive Platform for College English Intensive Reading Teaching Based on Cloud Service;intelligent Platform for College English Blended Teaching Based on Mobile Learning;preface.

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6th EAI international conference on Advanced Hybrid Information processing, ADHIP 2022

6th EAI International Conference on Advanced Hybrid Informat...

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6th EAI international conference on Advanced Hybrid Information processing, ADHIP 2022

ISBN: (纸本)9783031287862

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soft Security Resource Scheduling Issues in Cloud computing: A Review 6

Soft Security Resource Scheduling Issues in Cloud Computing:...

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6th IEEE international conference on signal processing, computing and Control, ISPCC 2021

作者： Himanshu Mangla, Neeraj MMDU Department Of Computer Science And Engineering Amabla Haryana Mullana133203 India

ISBN: (纸本)9781665425520

Cloud computing is emerging system which provides easier access to multiple applications through virtualized resources. It's a model of service which inspires the users to access the various resources without owing them as per the requirement over the web. Hence it is more convenient and cost efficient, but this feature brings the issue of data security with it. Under this paper, security challenges that could arouse and methods to overcome the same has been explored. In today's challenging world Cloud computing is equally important to any business but at the same time data privacy is also a big concern. Due to this reason cloud computing companies gives more importance to security of data. © 2021 IEEE.

关键词： Cloud computing

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A SAR Image Denoising Method for Target Shadow Tracking Task 22

A SAR Image Denoising Method for Target Shadow Tracking Task

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6th international conference on Digital signal processing, ICDSP 2022

作者： Huang, Yankun Sun, Guangcai Xing, Mengdao National Laboratory of Radar Signal Processing Xidian University China

ISBN: (纸本)9781450395809

the interpretation of Synthetic Aperture Radar (SAR) image is considered to be a challenging task, especially when tracking the target shadow in Video SAR (ViSAR), the speckle noise needs to be considered. Based on this, this paper proposes a SAR image denoising algorithm based on the improved wavelet threshold function. Different from the existing denoising methods, this algorithm combines the characteristics of hard threshold function and soft threshold function in traditional wavelet transform denoising, constructs a new threshold function, and improves the equivalent number of looks (ENL) of denoised SAR image. When the denoised image is applied to the tracking task, the target features are enhanced by k-means algorithm and binarization method, so as to improve the tracking accuracy. Experimental results show that the algorithm improves the tracking accuracy on the basis of ensuring the realtime performance of tracking and makes the tracking task highly robust to the noise of SAR image. © 2022 Association for computing Machinery. All rights reserved.

关键词： Synthetic aperture radar

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Optimization of computing Power Network Routing Strategies based on Multi-Agent soft Actor-Critic

Optimization of Computing Power Network Routing Strategies b...

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6th international conference on Intelligent computing and signal processing (ICSP)

作者： Zhongyue Chen Shicong Zhang Ying Tang Mengke Xu Xiaoqing Wu Minchao Ye Zhaojuan Zhang Yaping Qi Huijuan Lu Wanli Huo China Jiliang University Hangzhou Zhejiang China National (Hangzhou) Novel Internet Exchange Hangzhou Zhejiang China Division of Ionizing Radiation Metrology Hangzhou Zhejiang China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Despite rapid developments in cloud computing, big data, and artificial intelligence, the computing Power Network, as a new type of information infrastructure supporting the digital transformation and upgrading of various industries, faces significant challenges in efficiently scheduling, and managing computing and network resources. this paper introduces an optimization method for the computingRoute algorithm based on the Multi-Agent soft Actor-Critic algorithm, operating within a software-Defined Networking (SDN) architecture to address the efficiency issues in data transmission within the computing power network. the method leverages collaboration among multiple intelligent agents and employs deep reinforcement learning to optimize routing paths. Experimental results indicate that the MASAC algorithm, compared to traditional Actor-Critic algorithms, shows a 43.63 % improvement in stable average reward values, demonstrating better learning efficiency and performance. Furthermore, the soft policy updates, entropy regularization, and the use of target networks in the MASAC algorithm enhance its stability, improving training efficiency and performance. In performance comparisons with other computing power network routing strategies, the proposed computingRoute solution minimizes computing power requirements while reducing latency by 39.06% compared to DRL-TE and 21.42% compared to SmartPath. However, computingRoute exhibits a slightly higher packet loss rate than SmartPath.

关键词： Training Power demand Processor scheduling signal processing algorithms Packet loss Collaboration signal processing Routing Entropy software defined networking

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6th international conference on Big Data Cloud and Internet of things, BDIoT 2022

6th International Conference on Big Data Cloud and Internet ...

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6th international conference on Big Data Cloud and Internet of things, BDIoT 2022

ISBN: (纸本)9783031283864

the proceedings contain 49 papers. the special focus in this conference is on Big Data Cloud and Internet of things. the topics include: Knowledge Embeddings for Explainable Recommendation;Design of Blended Learning Course Based on SPOC for Primary School Teachers: Case of soft Skills;the Impact of the Online Flipped Classroom on the Learning Outcomes and Motivation of Nursing Students in Computer Science;digitizing Writing: An Empirical Exploratory Study Towards Students’ Writing Skill Fluency Improvement in ‘Padletosphere’;AraBERT with GANs for High Performance Fine-Grained Dialect Classification;genetic-Novelty Oversampling Technique for Imbalanced Data;neural Network for Arabic Text Diacritization on a New Dataset;processing Time Performance Analysis of Scheduling Algorithms for Virtual Machines Placement in Cloud computing Environment;Business - IT Alignment in Cloud Environment Comparative Study;machine Learning-Based Intrusion Detection System: Review and Taxonomy;reduce Cheating in e-Exams Using Machine Learning: State of the Art;comparative Study of Bayesian Optimization Process for the Best Machine Learning Hyperparameters;the Effect of Normalization and Batch Normalization Layers in CNNs Models: Application to Plant Disease Classifications;the Role of Ground Truth Annotation in Semantic Image Segmentation Performance for Autonomous Driving;fine-Tuning Pre-trained Vision Transformer Model for Anomaly Detection in Video Sequences;An Efficient Real-Time Moroccan Automatic License Plate Recognition System Based on the YOLO Object Detector;evaluation of Selected Machine Learning Models and Features for Electrical Consumption Prediction in Educational Institutions;Credit Card Fraud Detection Using SVM, Decision Tree and Random Forest Supervised Machine Learning Algorithms;SNDAE: Self-Normalizing Deep AutoEncoder for Recommendation;Intelligent Evaluation System Using NLP;retrospective Study and Evaluation of School Failure (Junior High School) in Scientific Subj

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Research and Design of Narrowband conference System Based on Hybrid Networking

Research and Design of Narrowband Conference System Based on...

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6th international conference on Intelligent computing and signal processing (ICSP)

作者： Zhikun Chen Yu Zhao Lu Wang Qianyun Ding Wenfang Yang Unit 91977 People Liberation Army of China Beijing China l Unit 91977 People Liberation Army of China Beijing China Sumavision Corporation in Beijing Beijing China

Based on the analysis of the current situation of video conferencing and the characteristics of satellite network environments, and in view of the environmental characteristics of ground satellite hybrid networking, this article proposes the research, design, and implementation of a narrowband conferencing system based on channel adaptation and modular processing ideas and methods, to improve the efficiency of remote audio and video communication in special network environments, and provide technical support for remote consultation, emergency relief, telemedicine, and mission support.

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