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检索条件"任意字段=3rd International Conference on Signal Processing and Machine Learning, SPML 2020"

共 729 条记录，以下是1-10 订阅

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Proceedings of the 2020 3rd international conference on signal processing and machine learning, spml 2020

Proceedings of the 2020 3rd International Conference on Sign...

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3rd international conference on signal processing and machine learning, spml 2020

ISBN: (纸本)9781450375733

The proceedings contain 22 papers. The topics discussed include: an efficient and robust aggregation algorithm for learning federated CNN;regeneration of gamma oscillations in large-scale neural network with complicated structure based on CUDA;support vector machine with neural network learning-based ontology for disaster risk management;an automatic scheme for optimizing the size of deep networks;feature selection using machine learning techniques based on search engine parameters;camera re-localization by training multi-dataset simultaneously via convolutional neural network;the impact of cloud computing infrastructure capability on enterprise agility: based on the perspective of IT business alignment;information-aware message passing neural networks for graph node classification;irregular meshes for color management;feature selection and classification methods for predicting search engine ranking;and deep learning for three types of keratitis classification based on confocal microscopy images.

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3rd international conference on signal processing and machine learning, CONF-spml 2023

3rd International Conference on Signal Processing and Machin...

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3rd international conference on signal processing and machine learning, CONF-spml 2023

The proceedings contain 64 papers. The topics discussed include: diffusion models-based data augmentation for the cell cycle phase classification;data augmentation by using GANs and image transformation in facial emotion classification;researches advanced in fine-grained image classification based on deep learning;performance analysis of attention mechanism and teacher forcing ratio based on machine translation;collaborative obstacle avoidance algorithm and simulation of swarm robots with limited viewing angle;the advance of underdetermined linear regression optimization based on implicit bias;bird audio recognition based on convolutional neural network;the configuration optimization of the plants in vertical farming by 3D modeling;robot navigation based on multi-sensor fusion;a study on the model predictive control based on convolutional neural network;channel capacity on visible light communication;and the gap between theoretical computational theories and application models.

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3rd international conference on machine Intelligence and signal processing, MISP 2021

3rd International Conference on Machine Intelligence and Sig...

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3rd international conference on machine Intelligence and signal processing, MISP 2021

ISBN: (纸本)9789811908392

The proceedings contain 67 papers. The special focus in this conference is on machine Intelligence and signal processing. The topics include: Internet of Things: A Survey on Fused machine learning-Based Intrusion Detection Approaches;Image Fusion-Based Watermarking in IWT-SVD Domain;on Twin Bounded Support Vector machine with Pinball Loss;traffic Rule Violation Detection System: Deep learning Approach;template-Based Thinning Method for Handwritten Gujarati Character’s Strokes and its Classification for Writer-Dependent Gujarati Font Synthesis;a Model on Intrusion Detection Using Firefly Algorithm and Classical machine learning;deep learning Framework Based on Audio–Visual Features for Video Summarization;a Comparative Study of Deep learning Models for Word-Sense Disambiguation;MultiYOLO: learning New YOLO Categories Without Full Retraining;Analysis of Fifteen Approaches to Automated COVID-19 Detection Using Radiography Images;vehicle Routing Problem Using Reinforcement learning: Recent Advancements;disease Detection of Plant Leaves with the Aid of Region Growing and Neural Network: A Comparative Analysis;a Web Application for Early Prediction of Diabetes Using Artificial Neural Network: A Comparative Study;machine learning Equipped Web-Based Disease Prediction and Recommender System;comparing the Predictive Accuracy of machine learning Algorithms for Neonatal Mortality Risk Classification;Extraction of Waterbody Using Object-Based Image Analysis and XGBoost;Deep learning-Based Image Retrieval in the JPEG Compressed Domain;fake News Detection Using Genetic Algorithm-Based Feature Selection and Ensemble learning;Application of SPSS for Forecasting of Renewable Energy as Future Energy in India;robust Multi-task Least Squares Twin Support Vector machines for Classification;human Emotion Classification Based on Speech Enhancement Using Neural Networks.

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Research on the application of machine learning in corporate public opinion monitoring and management 24

Research on the application of machine learning in corporate...

引用

3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Ma, Xiaohui School of Management Shanghai University Shanghai China

ISBN: (纸本)9798400710834

This article makes a point of the overall application of corporate public opinion monitoring and management technology based on machine learning. This work proves that by means of case analysis, the basic theories and methods of machine learning, it elaborates on how to use effective machine learning for large-scale public opinion data collection, processing, and analysis, and prediction. Considerable attention is paid to the way natural language processing techniques and sentiment analysis are applied in processing text data and how the models of machine learning, among other support vector machines, decision trees, and neural networks, bear upon implementation in real enterprise environments. Research results show that the level of efficiency and prediction accuracy will be greatly improved if the machine learning technique is applied during public opinion data processing, therefore effectively optimizing the strategy of public opinion response and management of the company. The effectiveness and application scenarios of each prediction model in public opinion analysis were verified through comparative analysis with multiple prediction models, which provided the scientific data support for the decision-making reference of the company. © 2024 Copyright held by the owner/author(s).

关键词： Prediction models

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Prediction of mechanical properties of Q345qE steel welded joints based on machine learning 24

Prediction of mechanical properties of Q345qE steel welded j...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Liu, Chengqing Hou, Xiaolong Liu, Lijun Qiao, Zhu Qin, Zhiqi Wang, Shengbao Company Limited Heilongjiang Harbin China School of Architecture and Civil Engineering Harbin University of Science and Technology Heilongjiang Harbin China Heilongjiang Provincial Transportation Planning and Design Institute Group Co. Ltd. Heilongjiang Harbin China

ISBN: (纸本)9798400710834

The mechanical properties of welded joints are the key indicators to evaluate the welding quality, which are mainly subject to the rationality of the welding process and the technical level of the welders. Traditionally, enterprises screen out the optimal welding scheme by implementing a large number of welding procedure qualification tests, but this method is costly and inefficient. In this study, the prediction model of tensile strength and yield strength of Q345 qE steel welded joints was established based on the machine learning algorithm of BP neural network. The results show that the prediction accuracy of the model is high, the R2 value is more than 0.96, and the relative error is controlled within ± 3MPa (tensile strength) and ± 5MPa (yield strength). This prediction method is expected to reduce the dependence on laboratory tensile tests, reduce experimental costs, and has significant application value for actual production. © 2024 Copyright held by the owner/author(s).

关键词： Tensile strength

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Enhancing Convolutional Models for Indoor Radio Mapping via Ray Marching

Enhancing Convolutional Models for Indoor Radio Mapping via ...

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2025 IEEE international conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Wu, Mengfan Skocaj, Marco Boban, Mate Munich Research Center Huawei Technologies Germany School of Electrical Engineering and Computer Science TU Berlin Germany

ISBN: (纸本)9798350368741

In this paper, we present an enhanced convolutional model for indoor radio map generation, focusing on the integration of a novel ray-marching feature. We describe our machine learning pipeline developed for the ICASSP 2025 signal processing Grand Challenge, specifically the First Indoor Pathloss Radio Map Prediction Challenge. Our method incorporates a ray-marching feature that, combined with a UNet architecture enhanced by dilated convolution layers, significantly improves indoor pathloss prediction accuracy. Our approach achieved a 3rd-place ranking in the challenge with a weighted RMSE of 10.33 on the test dataset. © 2025 IEEE.

关键词： feature engineering machine learning radio maps Wireless communications

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Shaft Rotation Monitoring Using Radar signal processing and Wavelet Transform 3rd

Shaft Rotation Monitoring Using Radar Signal Processing and ...

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3rd international conference on machine Vision and Augmented Intelligence, MAI 2023

作者： Valuyskiy, Denis Vityazev, Sergey Vityazev, Vladimir Ryazan State Radio Engineering University Gagarina. 59/1 Ryazan390005 Russia

ISBN: (纸本)9789819743582

This article discusses the problem of shaft rotation control for continuous testing of industrial equipment using a radar sensor. The FMCW radar with a frequency of 77 Hz is used to irradiate a rotating shaft and obtain information about the uniformity of its rotation. A test bench has been developed and radar reflections are recorded. Then the real signals are analyzed and an approach to signal processing and decision-making rules are proposed. The approach is based on wavelet transform and neural classification of rotating shifts with deep learning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Radar signal processing

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Hybrid EEG signal processing Framework for Driver Drowsiness Detection Using QWT, EMD, and Bayesian Optimized SVM 3

Hybrid EEG Signal Processing Framework for Driver Drowsiness...

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Sardesai, Shilpa Gedam, Rahul Pune India Lcit Department of Electronics and Telecommunication Bilaspur India

ISBN: (纸本)9798331508456

Drowsiness among drivers poses an urgent safety problem in road transportation because it creates serious risks to both drivers and their passengers. Carrying out prolonged driving operations creates a mind state between full wakefulness and sleep. The research presents a new supervised learning approach to evaluate sleep stages which helps detect driver sleepiness and trigger prompt alerts. A deep feature extraction system based on QWT with time-frequency scalogram and EMD artifact removal generates features from EEG signals. The system uses evaluation of decomposition levels' energy measurements to build Energy Vectors which lead to the processing of each EEG signal into feature vectors. Data classification in this research occurs through implementation of the BO-SVM classifier which features Bayesian optimization. The BO-SVM classifier delivers exceptional accuracy results because it reaches 99.17% maximum accuracy beyond typical SVM classifier performance levels. This paper combines signal processing methods with machine learning techniques which result in advanced EEG data-based sleep stage diagnosis to enhance driver safety. © 2025 IEEE.

关键词： Image reconstruction

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sEMG signal processing and Recognition Based on CNN 3rd

sEMG Signal Processing and Recognition Based on CNN

引用

3rd international conference on machine learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Tian, Zimo Xu, Guangjie Cai, Senwu He, Xuansen Guangzhou College of Commerce Guangzhou511363 China College of Information Science and Engineering Hunan University Changsha410082 China

ISBN: (纸本)9789819624676

Extraction and processing of surface electromyography (sEMG) signals play an important role in medical rehabilitation, artificial limb control and other applications. This paper proposes a new method for sEMG signal processing based on convolutional neural networks (CNN). Firstly, the time-domain feature extraction method is used to extract the features of sEMG signals. Then, a CNN model is constructed for identifying and processing sEMG signals. The parameters of the model are calibrated based on the sEMG dataset to find the most suitable model parameters for the objective of this paper, achieving optimization of the model. The constructed CNN network is applied to NinanPro dataset for simulation and experiment, and the results show that the optimized CNN model proposed in this paper has a high accuracy rate for sEMG signal recognition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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3rd international conference on machine Vision and Augmented Intelligence, MAI 2023

3rd International Conference on Machine Vision and Augmented...

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3rd international conference on machine Vision and Augmented Intelligence, MAI 2023

ISBN: (纸本)9789819743582

The proceedings contain 76 papers. The special focus in this conference is on machine Vision and Augmented Intelligence. The topics include: Survey on Robustness of Deep learning Techniques on Adversarial Attacks in WBAN;synergizing Collaborative and Content-Based Filtering for Enhanced Movie Recommendations;exploring Transformer-Based Approaches for Hyperspectral Image Classification: A Comparative Analysis;deep learning for Cognitive Task and Seizure Classification with Hilbert–Huang Transform and Variational Mode Decomposition;tracking of Ship and Plane in Satellite Videos Using a Convolutional Regression Network with Deep Features;Tumor Detection and Analysis from Brain MRI Images Using Deep learning;software Maintenance Prediction Using Stack Ensemble Deep learning Algorithms;resource Allocation in 6G Network for High-Speed Train Using D2D Outband Communication;controlling the Band-to-Band Tunneling Effect in Charge Plasma Based Dopingless Transistor;Comparison of Different CIC Filter Architectures on the Basis of a Novel Parameter Called Noise Factor for Sigma-Delta Based ADCs;the Scientific Analysis on Effective Yoga Posture Recognition Techniques;impact of Gamma Rays on Emerging Devices for Photonic Applications;shaft Rotation Monitoring Using Radar signal processing and Wavelet Transform;gysel Power Divider Miniaturization Using an Inter-Digital Capacitor-Based Slow-Wave Structure;noise Estimation and Removal in Fundus Images Using Pyramid Real Image Denoising Network;evaluation of Hybrid Encryption Method to Secure Healthcare Data;multimodal Face Recognition System Using Hybrid Deep learning Feature;Classification of Copy and Move Image by Using HELM-FSK Method: An Efficient Approach;analysis of Energy Efficient Smart Home Based on IoT System;role of Explainable Artificial Intelligence Approaches in Cybersecurity.

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