Search Results - (( variable optimization method algorithm ) OR ( feature classification system algorithm ))
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Besides, this thesis developed a hybrid filter method to enhance the performance of the IFS. IFS served as filter together with an Ant Colony Optimization System (ACO) as a metaheuristic form the hybrid system. …”
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A genetic algorithm based fuzzy inference system for pattern classification and rule extraction
Published 2023“…Therefore, our proposed GA-FIS method will first define the membership functions with logical interpretation which is amendable by domain experts to human understanding, and then genetic algorithm serves as an optimization tool to construct the best combination of rules in fuzzy inference system that can achieve higher classification accuracy and gain better interpretability. …”
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Statistical band selection for descriptors of MBSE and MFCC-based features for accent classification of Malaysian English / Yusnita M. A. ...[et al.]
Published 2013“…This paper proposes an efficient way of analyzing the ethnical accent using statistical knowledge of log-energies of fourier transformed derived mel-filter banks. A simple algorithm to select bands so called statistical band selection (SBS) method using smallest variances within class scores was developed to optimize the presentation of speech features. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed segmentation is evaluated on real-world clinical data using publicly accessible benchmark clinical liver datasets containing one of the highest numbers of tumors and pathological livers utilized for liver tumor and vasculature segmentation. The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…However, the ACO suffers from premature convergence which leads to poor feature subset. Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…A critical step in developing such intelligent systems is the feature extraction process. Feature extraction is essential in classification, especially for data sources in the form of images. …”
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Automated plant classification system using a hybrid of shape and color features of the leaf
Published 2016“…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm
Published 2014“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…This condition is attributed to the increasing number of audit data features and the decreasing performance of human-based smart intrusion detection systems regarding classification accuracy, false alarm rate, and classification time. …”
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An accurate infant cry classification system based on continuos hidden Markov model
Published 2023Subjects:Conference Paper -
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Application of the bees algorithm to the selection features for manufacturing data
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Efficient and low complexity modulation classification algorithm for MIMO systems
Published 2015“…This study develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed Multiple-Input Multiple-Output (MIMO) systems employing two Higher Order Cumulants (HOCs) of the estimated transmit signal streams as discriminating features and a multiclass Support Vector Machine (SVM) as a classification system. …”
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SVM for network anomaly detection using ACO feature subset
Published 2016“…This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…Various artificial neural network (ANN) architectures were applied to the datasets to verify the proficiency of various combinations of input variables, learning optimization methods and different numbers of neurons on the hidden layer by MATLAB 2014a software. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…In implementing an automation plantation system, a plant health classification system is necessary in monitoring the health of the plants. …”
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