يعرض 1 - 20 نتائج من 295 نتيجة بحث عن 'using classification machine', وقت الاستعلام: 0.08s تنقيح النتائج
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    FPGA-Based Network Traffic Classification Using Machine Learning حسب Elnawawy, Mohammed

    منشور في 2019
    "…A Master of Science thesis in Computer Engineering by Mohammed Elnawawy entitled, “FPGA-Based Network Traffic Classification Using Machine Learning”, submitted in November 2019. …"
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    doctoralThesis
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    FPGA-Based Network Traffic Classification Using Machine Learning حسب Elnawawy, Mohammed

    منشور في 2020
    "…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …"
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    article
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    Machine learning approach for the classification of corn seed using hybrid features حسب Aqib Ali (19680145)

    منشور في 2020
    "…The nine optimized features have been acquired by employing the correlation-based feature selection (CFS) technique with the Best First search algorithm. To build the classification models, Random forest (RF), BayesNet (BN), LogitBoost (LB), and Multilayer Perceptron (MLP) were employed using optimized multi-feature using (10-fold) cross-validation approach. …"
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    COVID-19 Tweets Classification during Lockdown Period Using Machine Learning Classifiers حسب Syed Ali Jafar Zaidi (19505617)

    منشور في 2022
    "…Support vector machine (SVM), random forest (RF), decision tree (DT), and k-nearest neighbor (KNN) were used for classification, while AdaBoost and convolutional neural network (CNN) were utilized for future effects. …"
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    An efficient approach for textual data classification using deep learning حسب Abdullah Alqahtani (7128143)

    منشور في 2022
    "…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …"
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    Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques حسب Amith Khandakar (14151981)

    منشور في 2022
    "…Machine learning approaches applied to such infrared images may have utility in the early diagnosis of diabetic foot complications. …"
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    The automation of the development of classification models and improvement of model quality using feature engineering techniques حسب Sjoerd Boeschoten (17347045)

    منشور في 2023
    "…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …"
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    Improved Machine Learning for Multiclass Fault Classification in Industrial Processes حسب Khaled Dhibi (16891524)

    منشور في 2025
    "…Traditional machine learning models often struggle in such settings. …"
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    Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS حسب Khan, Malik Nasir Afzal

    منشور في 2025
    "…For a comprehensive evaluation, the acquired fNIRS data are classified using a variety of machine-learning approaches. Linear discriminant analysis (LDA) showed a maximum accuracy of 60%, whereas non-augmented data classified by a convolutional neural network (CNN) provided the highest classification accuracy of 73%. …"
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    article
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    A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 حسب Al-Manaseer, Hitham

    منشور في 2022
    "…In this study, the possibility of using and applying the capabilities of artificial intelligence (AI) and machine learning (ML) to increase the effectiveness of Internet of Things (IoT) and big data in developing a system that supports decision makers in the medical fields was studied. …"
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    Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach حسب Zubair Saeed (19325647)

    منشور في 2024
    "…DL techniques have become more and more popular in current research on brain tumor detection. Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. …"