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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Single classifer vs. ensemble machine learning approaches for mental health prediction
Published 2023“…One of the promising approaches to achieving fully automated computer-based approaches for predicting mental health problems is via machine learning. As such, this study aims to empirically evaluate several popular machine learning algorithms in classifying and predicting mental health problems based on a given data set, both from a single classifier approach as well as an ensemble machine learning approach. …”
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An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…It is found that these findings would improve the early diagnosis methods of cancer classification.…”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.]
Published 2023“…RFA as a machine learning classification model has the potential to provide more accurate predictions than traditional methods. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…So that the study can have implications for cyber experts to be able to prevent malware attacks early. While further research requires a special algorithm to improve malware attack detection, in addition to KNN, SVM and Neural Network. …”
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Early Detection Of ADHD Among Children Using Machine Learning
Published 2023“…This abstract explores the significance of early ADHD detection, the potential of fMRI for ADHD diagnosis, and the role of machine learning in facilitating early identification. …”
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Accuracy and performance analysis for classification algorithms based on biomedical datasets
Published 2021“…This paper presents and analyzes five different machine learning (ML) algorithms: Function-based Neural Network (MLP) algorithm. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., â��The Plant Village Datasetâ�� and perform classification into only two classes in potato leaves. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., â��The Plant Village Datasetâ�� and perform classification into only two classes in potato leaves. …”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…We hope that these our results would help improve the classification of breast tissue to allow the early prediction of cancer susceptibility.…”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…Integrating SSA and SVM machine learning algorithms improves decision-making processes, leading to better crop yield through early detection and timely nutrient management. …”
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