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检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1863 条记录，以下是231-240 订阅

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Research and application of Different machine learning Algorithms in ILPD Risk Prediction Model 3

Research and Application of Different Machine Learning Algor...

引用

3rd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： He, Huayi Sichuan University School of Computer Science Chengdu China

ISBN: (纸本)9798350398410

In recent years, the development of artificial intelligence technology in the medical field has gained increasing attention. Today, machine learning techniques have a strong potential especially in the automatic diagnosis of various diseases. Several machine learning algorithms, such as Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Gradient Boosted Decision Tree (GBDT), XGBoost (XGB), LightGBM (LGBM), and K-Nearest Neighbors (KNN), were used in this study to construct a liver disease risk prediction model. The classification algorithms were applied to Indian Liver Patient Dataset (ILPD) collected from UCI machine learning repository, and then the performance of different classification algorithms was evaluated by performance parameters such as accuracy, recall, F1-score, and AUC. The accuracy of LR, DT, RF, GBDT, XGB, LGBM and KNN can be derived from the experiments as 0.6867, 0.7651, 0.8193, 0.7831, 0.7651, 0.8413, and 0.7590, respectively. After comparison, it is found that the prediction performance of LGBM is superior to other machine learning algorithms for the ILPD dataset. The machine learning model has important implications in improving patient survival and helping physicians to make effective clinical decisions. © 2023 IEEE.

关键词： Decision trees

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application of machine learning for Improving the Algorithm for Capturing, Orienting and Placing an Object with 6-Axis Robot and 2d Visual Inspection Camera 3

Application of Machine Learning for Improving the Algorithm ...

引用

3rd international Congress on Human-computer Interaction, Optimization and Robotic applications, HORA 2021

作者： Hristov, Vladimir Kostov, Boris Technical University of Sofia Faculty of Automatics Department of Electrical Motion Automation Systems Sofia Bulgaria

ISBN: (纸本)9781665440585

The current paper presents the implementation of machine learning to improve the algorithm for taking a part with a specific marker from a 6-axis robot, by serve it to a 2D camera for visual inspection and its correct orientation based on information received from the camera and placement on another part with a pre-marked marker direction. The aim of the present development is to increase the efficiency of automated production of electronic products. After the introduction of machine learning in the algorithm for determining distortions, injuries or other damage to the part, an improvement was achieved in the quality of the processed parts and a reduction of production waste by up to 30%, which led to an increase in system efficiency by 25%. © 2021 IEEE.

关键词： Cameras

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Spam and Non-Spam URL Detection using machine learning Approach 3

Spam and Non-Spam URL Detection using Machine Learning Appro...

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Raj, Ritu Singh Kang, Sandeep University Institute of Engineering Computer Science & Engineering Chandigarh University Mohali India

ISBN: (纸本)9781665494991

In the modern world, where everyone is connected with internet, a threat has always surrounded every internet user which steals user credentials by various means;this threat is known as Phishing. The attacker acts as a trustworthy agent and steals victim's credentials or personal details. This information is then used for illegal purpose which may result in identity theft or financial loss. This project provides a better understanding on how phishing attacks are carried out by attackers and how these attacks are detected by websites that uses various detection methods. A tool is designed using machine learning and deep neural net which classify Uniform Resource Locator (URLs) as phishing or legitimate URL. Dataset is collected from various resources that contain phishing and legitimate URLs of websites and then these datasets are provided to the neural net for supervised training. Various classification algorithms are, then, applied on these datasets and then accuracy of these algorithms is predicted. © 2022 IEEE.

关键词： Websites

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Heterotropia diagnosis with smartphone using machine learning and computer vision 3

Heterotropia diagnosis with smartphone using machine learnin...

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3rd international conference on Contemporary Computing and Informatics, IC3I 2018

作者： Gupta, Harsh Moder School Department of Computer Science New Delhi India

ISBN: (纸本)9781538668948

In this paper, a deviation-based algorithm is proposed which exploits the power of TensorFlow, OpenCV, and machine learning to diagnose four forms of heterotropia - esotropia, exotropia, hypertropia and hypotropia. The mechanism developed for lateral, vertical, and angular deviation has been tested for K-Nearest-Neighbors (KNN), Support Vector machine (SVM), and a trained neural network, based on 6 features. Finally, the accuracy, specificity, and sensitivity of the 2 MLC and convolutional neural network (CNN) was tested in a study of 337 users with and without heterotropia. Eyeris, an Android based application, has been developed as a proof of concept for this paper. The results yielded highest accuracy for SVM-based classification. © 2018 IEEE.

关键词： computer vision

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Analysis Of machine learning Algorithm for Prognostication of Parkinson's Disease Using Speech Articulation 3

Analysis Of Machine Learning Algorithm for Prognostication o...

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3rd international conference for Emerging Technology, INCET 2022

作者： Fathima, G Babu, Tharunaa Shoban Srimaan, A Shubhakar, B C Adhiyamaan College of Engineering Department of Computer Science and Engineering Hosur India

ISBN: (纸本)9781665494991

The disease named Parkinson's is a popular health disease among humans that is progressively increasing day by day and has had its effects on many countries. Thus, it is very important to diagnose the disease at the starting stage which has been a challenging action for the researchers, as the symptoms to diagnose the disease differ from person to person and it can exist in people from mid age to older age. In this paper the performance of different models such as adaboost classifier, logistic regression, support vector classifier and decision tree classifier has been evaluated using various metrics i.e. accuracy, precision, specificity. It primarily focuses on the symptoms of speech articulation problems in persons that are being diagnosed with Parkinson's and develops the model using Support Vector machine. To forecast the diagnosis of Parkinson's, the Boruta feature choosing technique is utilised for the determination of the most essential features comparing to all the other features. © 2022 IEEE.

关键词： Support vector machines

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Proceedings of 3rd international conference on Intelligent Engineering and Management, ICIEM 2022

Proceedings of 3rd International Conference on Intelligent E...

引用

3rd international conference on Intelligent Engineering and Management, ICIEM 2022

ISBN: (纸本)9781665467568

The proceedings contain 168 papers. The topics discussed include: design for ergonomics: application of single- passenger electric car via design of experiments;detection of breast cancer using machine learning and deep learning methods;automobile insurance fraud detection: an overview;a survey on detection of lung cancer using different image processing techniques;deep learning methods for automatic number plate recognition system: a review;skin cancer detection using machine learning: a survey;transforming education system through artificial intelligence and machine learning;model for retailers with price dependent demand rates;neuromarketing: an emerging domain in the formal education system;design of dual slot microstrip antenna for wireless application;analysis of ancillary services provided by distributed energy resources in smart distribution grid;and grey scale image skeletonization of vein pattern using Hausdroff image binarization technique in biometric security system.

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Detecting anomalies in application performance management system with machine learning algorihms 3

Detecting anomalies in application performance management sy...

引用

3rd IEEE international conference on Electronic Information Technology and computer Engineering, EITCE 2019

作者： Shi, Yujun Miao, Kehua Xiamen University Department of Automation Xiamen China

ISBN: (纸本)9781728135847

application performance management which is short for APM is a real-time monitoring of enterprise systems to implement a systematic solution to application performance management and fault management. APM is a relatively new network management direction. It mainly refers to monitoring and optimizing key business applications of enterprises, improving the reliability and quality of enterprise applications, ensuring users to get good services and reducing total cost of ownership (TCO). If a company's business-critical applications are powerful, they can increase competitiveness and achieve business success. Therefore, enhancing application performance management (APM) can generate huge business benefits. This paper explores the application of machine learning-based anomaly detection algorithm in APM system by analyzing continuous time series data from actual network systems. © 2019 IEEE.

关键词： Anomaly detection

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Bird's Nest Detection Algorithm for Transmission Lines Based on Deep learning 3

Bird's Nest Detection Algorithm for Transmission Lines Based...

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3rd international conference on computer Vision, Image and Deep learning and international conference on computer Engineering and applications, CVIDL and ICCEA 2022

作者： Ge, Zhao Li, Hongwen Yang, Rui Liu, Haifeng Pei, Shaotong Jia, Zhihui Ma, Ziru State Grid Xiong'an New Area Electric Power Supply Company Baoding China North China Electric Power University Hebei Provincial Key Laboratory of Power Transmission Equipment Security Baoding China

ISBN: (纸本)9781665459112

The bird's nest on the power transmission tower may cause the occurrence of bird flash accidents and threaten the safe and reliable operation of the power grid. The realization of the independent identification and positioning of the bird's nest has always been a research hotspot. With the gradual deepening of the application of UAV inspection, higher requirements are put forward for the accuracy and speed of the bird's nest recognition algorithm. This paper proposes a bird's nest defect recognition method based on YOLOv5, which is composed of backbone network, FPN and YOLO head. After multiple rounds of training on the construction of the bird's nest defect database and model of the transmission line, the independent identification and positioning of the bird's nest has been realized. The results show that the recognition rate of the YOLOv5 model for the bird's nest can reach 83.4%, and the FPS can reach 85.32. The recognition algorithm based on YOLOv5 proposed in this paper can meet the real-time and accuracy requirements of UAV inspection for target detection. © 2022 IEEE.

关键词： Electric lines

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Graph Convolutional Extreme learning machine Autoencoder for Graph Embedding 3

Graph Convolutional Extreme Learning Machine Autoencoder for...

引用

3rd international conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Lin, Xinyi Chen, Xiaoyun Lin, Yanming College of Mathematics and Statistics Fuzhou University Fujian China

ISBN: (纸本)9798350331578

The purpose of graph embedding is to encode the known node features and topological information of graph into low-dimensional embeddings for further downstream learning tasks. Graph autoencoders can aggregate graph topology and node features, but it is highly dependent on the gradient descent optimizer with a large iterative learning time, and susceptible to local optimal solutions. Thus, we propose Graph Convolutional Extreme learning machine Autoencoder. To address the limitation that the extreme learning machine autoencoder cannot use topological information, the graph convolution operation is introduced between the input layer and the hidden layer to improve the representation ability of the graph embedding obtained. Experiments of link prediction and node classification on 5 real datasets show that our method is effective. © 2023 IEEE.

关键词： Classification (of information)

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A Study of Various Word Embeddings in Deep learning 3

A Study of Various Word Embeddings in Deep Learning

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3rd international conference for Emerging Technology, INCET 2022

作者： Shah, Parth Shah, Smit Joshi, Saurav K.J. Somaiya College of Engineering Computer Engineering Mumbai India

ISBN: (纸本)9781665494991

With the number of users and reviews rising on the internet, and the liberty was given to post anything on it, it is still a major issue to identify the sentiment of the reviews. The traditional machine learning models are taking a lot of computational time to get desired results. The advancement in the field of deep learning has left people wondering whether it would provide better results for such applications. Word Embeddings play a huge role in the classification of text, as they represent similar meaning documents with equivalent representation. The result of the deep learning model trained on a particular set of data depends upon the sort of word embedding used. In this work, we intend to present a study of various embeddings like GloVe, BERT, Word2vec, and Fast-text using a proposed model. The research was conducted on the IMDB movie review dataset and the result displayed that GloVe embeddings produced the best result with an accuracy of 87.936 % on our proposed model. © 2022 IEEE.

关键词： Embeddings

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