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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…The issue has been extensively addressed in uncountable researches and using various techniques, of which a commonly used technique is that based on detecting intrusions in contrast to normal network traffic and the classification of network packets as either normal or abnormal. …”
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Neural network paradigm for classification of defects on PCB
Published 2003“…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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Face recognition for varying illumination and different optical zoom using a combination of binary and geometric features
Published 2020“…Several binary conversion-based methods have used an adaptive thresholding technique to improve their performance under illumination variation conditions because of its robustness. …”
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Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm
Published 2015“…We then review the state-of-the-art US-based CAD techniques that utilize a range of image texture based features like entropy, Local Binary Pattern (LBP), Haralick textures and run length matrix in several automated decision making algorithms. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Vehicle classification technique for automated road traffic census
Published 2014“…This thesis proposes the development of vehicle classification technique for automated road traffic census prototype to replace manually vehicle classification by applying morphological techniques for image classification. …”
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Final Year Project Report / IMRAD -
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification
Published 2021“…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…The second objective is to conduct a supervised and binary ensemble machine learning technique for classification. …”
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Automatic classification of medical x-ray images
Published 2013“…Image representation is one of the major aspects of automatic classification algorithms. In this paper, different feature extraction techniques have been utilized to represent medical X-ray images. …”
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Segmentation of Lung Region in Computed Tomography (CT) Images
Published 2015“…Segmentation of lung region in lung CT scan images is an important pre-processing technique prior automatic detection and classification of emphysema disease. …”
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Final Year Project -
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Hybrid ensemble learning techniques for intrusion detection systems in Internet of Things security
Published 2025“…The first technique employed the XGBoost and LightGBM algorithms to solve a binary classification problem across seven different datasets. …”
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UMK Etheses -
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Text Extraction Algorithm for Web Text Classification
Published 2010“…Web pages need automatic classification techniques with high classification accuracy. …”
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Texture Classification of lung computed tomography (CT) using local binary patterns (LBP)
Published 2015“…In this work, we proposed an LBP-based lung classification algorithm. The local binary pattern (LBP) is one of the feature extraction technique that can be used in classify the image. …”
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Final Year Project -
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Hybrid binary whale with harris hawks for feature selection
Published 2022“…This study introduces the BWOAHHO memetic technique, which combines the binary hybrid Whale Optimization Algorithm (WOA) with Harris Hawks Optimization (HHO). …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. …”
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