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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11-20 订阅

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2024 3rd international conference for Advancement in Technology, ICONAT 2024

2024 3rd International Conference for Advancement in Technol...

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3rd international conference for Advancement in Technology, ICONAT 2024

ISBN: (纸本)9798350354171

The proceedings contain 326 papers. The topics discussed include: design of low current driver for digital attenuator;a comprehensive metric for evaluating object-oriented software complexity;examining the role of error control in ATM networks;an intelligent method for performance of air conditioning system and vehicle fuel economy trade-offs for a hybrid electric vehicle using SA-CNN-LSTM mode;AI-enhanced cloud security framework for IoT networks using a predictive analytics approach;design and analysis of 1710-1880 MHz power amplifier for n3-5G new radio frequency band;duplicate detection in Quora question pairs using machine learning;and advanced machine learning frameworks for multimodal image and speech signal processing.

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The classification of human brain tumors with machine learning 3

The classification of human brain tumors with machine learni...

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

作者： Ma, Zihan Lin, Ziwei United International College Beijing Normal University Hong Kong Baptist University 2000 Jintong Road Tangjiawan Zhuhai China School of Computer Science and Technology Zhuhai College Jilin University Jinwan District Zhuhai China

This paper aims to report human brain tumor classification based on machine learning. Brain tumors have long been regarded as one of the deadliest tumors. Conventionally, without the assistance of automation tools, brain tumor diagnosis is a skill-demanding work for the doctors and a time-consuming burden on the medic system. Applying machine learning to clinical medicine and classifying brain tumors enables physicians to increase their diagnosis correctness and allows the health system to treat more patients. This paper covers the methods used in the research: the dataset, network models, algorithm, and implementation. The experiment results and discussion section follow this. Focusing on comparing and discussing convolutional neural networks' performance and resource consumption under different network settings and network models. In the experiment, by feeding the MRI images to the network, the network automates the results indicating whether a tumor is detected in the image and classifies the underlying tumor. The experiment results indicate machine learning's great accuracy of 93.38 percent in classifying brain tumors and the significant correlations between the model's performance and resource cost, and network settings as well as model complexity. © Published under licence by IOP Publishing Ltd.

关键词： Tumors

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A Review of signal processing Techniques for Detection and Classification of Faults in Transmission lines 3

A Review of Signal Processing Techniques for Detection and C...

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3rd international conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2024

作者： Agarwal, Hiya Tiwari, Ravi Shankar Sharma, Jai Prakash GLA University Department of Electrical Engineering Mathura281406 India

ISBN: (纸本)9798350309409

In a contemporary power system, the prompt and precise removal of faults occurring on high-voltage transmission lines is of utmost importance. This research explores the categorization and pinpointing of faults in the protection of power transmission lines based on signal processing techniques. The paper reviews the effective, promising, and modern approaches for fault detection such as machine learning (ML) and artificial intelligence (AI) methodologies. It also highlights the application of Wide Area Measurement (WAM), and Phasor Measurement Unit (PMU) in the protection of transmission lines. © 2024 IEEE.

关键词： Wavelet transforms

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Design of a Free Trade Zone Data Management and Analysis Platform Based on Computer machine learning Technology 3

Design of a Free Trade Zone Data Management and Analysis Pla...

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3rd international signal processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Liu, Chunyang Liu, Yi Wang, Shuli School of Economics Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350307023

This study is dedicated to architecting a data management and analysis platform, integrating advanced computer technologies and machine learning algorithms. Traditional approaches often fall short in handling and analyzing vast data sets. Thus, this paper proposes an innovative solution: enhancing data processing efficiency and precision through machine learning technologies. The research thoroughly examines the application of machine learning in data management, including the selection of appropriate algorithms, effective model training and optimization, and their integration into a user-friendly platform. The platform's design aims to deliver more accurate data analysis, supporting informed decision-making. © 2023 IEEE.

关键词： Information management

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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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Diverse Image processing Techniques for machine learning Methods 3

Diverse Image Processing Techniques for Machine Learning Met...

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3rd IEEE international conference on Intelligent Techniques in Control, Optimization and signal processing, INCOS 2024

作者： Bhagya, A. Perumal, S. Vels Institute of Science Technology and Advanced Studies Department of Computer Science Tamil Nadu Chennai India

ISBN: (纸本)9798350361186

machine learning is a trending topic in the area of computer vision, which makes the machine able to learn about it without being expressly programmed using various algorithms. When a model is designed to predict future-based on historical data using machine learning algorithms, data is vital because high quality data is needed to run the model efficiently and to predict highly accurate results. machine learning algorithms receive data in many forms, like audio (speech recognition), images (feature recognition), numeric data (like height and weight) etc. When it comes to computer vision, the machine learning algorithms must be able to understand the image data, and before the images are processed to the algorithms it should be pre-processed (cleaned and set to the desired format) using various image pre-processing techniques. This research paper presents various image processing techniques, literature reviews on various image processing techniques and image PSNR value after applying median filter, grayscale filter and box filters. © 2024 IEEE.

关键词： Median filters

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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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Performance analysis of attention mechanism and teacher forcing ratio based on machine translation 3

Performance analysis of attention mechanism and teacher forc...

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

作者： Lu, Chengsong Department of Computer Science The University of Sheffield SheffieldS10 2TN United Kingdom

The Seq2seq model has the characteristics that the encoder is used to analyze the input sequence, and the decoder is used to generate the output sequence, which is very suitable for the characteristics of machine translation tasks, making it achieve advanced performance in the field of machine translation. In addition, the attention mechanism has achieved remarkable results in many kinds of natural language processing tasks. The combination of seq2seq model and attention mechanism is the critical research direction in machine translation. To compare the effects of different attention mechanisms on the performance of machine translation models, this paper selects two classical attention mechanisms, including Synthetic Attention and Muti-head Attention, to test machine translation tasks. In addition, for another critical set of the sequence model, teacher-forcing, this paper also tests the influence of different teacher-forcing thresholds on the model performance. The experimental results show that Muti-head Attention has apparent advantages over Synthetic Attention. In addition, the reasonable choice of teacher-forcing also affects the stability of the model in the real environment. © Published under licence by IOP Publishing Ltd.

关键词： machine translation

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Prediction and classification of skin melanoma cancer using active hybrid machine learning technique 3

Prediction and classification of skin melanoma cancer using ...

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

作者： Saravanan, S. Sathishkumar, V.E. Rajalakshmi, N.R. Sukumar, R. Muthukumaran, V. Department of CSE Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Avadi Chennai India Department of Industrial Engineering Hanyang University Seoul Korea Republic of School of Computing Science and Engineering VIT Bhopal University Bhopal-Indore Highway Kothrikalan MP Sehore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur603203 India

Melanoma is a dangerous skin cancer that may spread if not detected early. Thus, the medical industry has evolved with automated diagnostic tools that may assist physicians and even regular people diagnose an illness. Here, we provide a combined method for identifying melanomas on the skin. For our proposed approach, we make use of three forecasts. This problem was solved by training a neural network and two-learning machine classifiers on data describing the borders, textures, and colours of skin lesions. These tactics are combined for maximum effectiveness by majority voting. Tests show that using all three methods simultaneously improves precision. © Published under licence by IOP Publishing Ltd.

关键词： Dermatology

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A TCAD Augmented machine learning Based Drain Current Model for InGaAs FinFETs 3

A TCAD Augmented Machine Learning Based Drain Current Model ...

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3rd IEEE international conference on Applied Electromagnetics, signal processing, and Communication, AESPC 2023

作者： Maity, Arya Maity, Subir Kumar Odisha Bhubaneswar751024 India

ISBN: (纸本)9798350358742

In this paper, we describe a framework for model development of InGaAs FinFET based on machine learning. An artificial neural network is used to create the model, and TCAD simulation data was used to train it. The model accurately and efficiently captures changes in gate length, drain, and gate bias voltages. In order to enable circuit simulation utilizing the SPICE environment, the trained model is exported to the Verilog-A language, and circuit simulation is demonstrated. © 2023 IEEE.

关键词： Semiconducting indium gallium arsenide

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