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1
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
2
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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3
Comparative study of machine learning algorithms in data classification
Published 2025“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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Final Year Project / Dissertation / Thesis -
4
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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5
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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6
Evaluation of fall detection classification approaches
Published 2012“…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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Conference or Workshop Item -
7
Financial time series predicting using machine learning algorithms
Published 2013“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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8
Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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9
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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10
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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11
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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12
Neural network paradigm for classification of defects on PCB
Published 2003“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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13
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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14
Herbs recognition based on chemical properties using machine learning algorithm
Published 2023“…This method has demonstrated promising results in identifying herb species, and the classification method based on machine learning algorithms has proven successful in recognizing and distinguishing herb species…”
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15
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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16
Support vector classification of remote sensing images using improved spectral Kernels
Published 2008“…A very important task in pattern recognition is the incorporation of prior information into the learning algorithm. …”
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17
Face recognition using eigenfaces and smooth support vector machine
Published 2011“…They are applied here to generate and solve an unconstrained smooth reformulation of the support vector machine for pattern classification using a completely arbitrary kernel. …”
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Undergraduates Project Papers -
18
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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19
Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Final Year Project / Dissertation / Thesis -
20
Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction
Published 2019“…The extracted features are then fed into the machine learning algorithm for classification process. Four popular machine learning algorithms include k-nearest neighbor (KNN), linear discriminate analysis (LDA), Naïve Bayes (NB) and support vector machine (SVM) are used in evaluation. …”
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