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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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Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter
Published 2015“…In this research, a Gabor-based emphysema classification algorithm is proposed. …”
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Final Year Project -
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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4
Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…Based on its simplicity, the K-means algorithm has been used in many fields. …”
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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SVM for network anomaly detection using ACO feature subset
Published 2016“…Intrusion detection systems are developed on the bases of two different detection techniques, signature-based technique and anomaly-based technique. …”
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7
An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks
Published 2020“…Many algorithms have been developed for automated electrocardiogram (ECG) classification. …”
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Effective gene selection techniques for classification of gene expression data
Published 2005“…Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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Thesis -
9
Classification of Rheumatoid Arthritis using Machine Learning Algorithms
Published 2019“…In this preliminary work, ensemble algorithms such as bagging, AdaBoost and random subspace with base classifier such as random forest and SVM were trained and tested using the assessment criteria such as accuracy, precision, sensitivity and AUC using Weka tool. …”
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Classification of Rheumatoid Arthritis using Machine Learning Algorithms
Published 2019“…In this preliminary work, ensemble algorithms such as bagging, AdaBoost and random subspace with base classifier such as random forest and SVM were trained and tested using the assessment criteria such as accuracy, precision, sensitivity and AUC using Weka tool. …”
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Development of cardioid based graph ECG heart abnormalities classification technique
Published 2015“…Unique features were extracted using the Pan Tompkins algorithm, later Cardioid based graph was formed as the result of the differentiation process. …”
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Detection of corneal arcus using rubber sheet and machine learning methods
Published 2019“…To ensure the obtained classification results are robust and stable the cross validation (CV) technique is used. …”
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Thesis -
13
An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…There are different techniques used in RS. Some works are based on user past knowledge known as Content Based (CB) while more popular techniques referred to as neighborhood models (CF and MF) are based on finding similar users for recommendation. …”
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Face authentication system based on FDA and ANN.
Published 2010“…In addition, the photometric normalization techniques based on Histogram Equalization and Homomorphic Filtering are used to improve the appearance of the face. …”
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Quranic diacritic and character segmentation and recognition using flood fill and k-nearest neighbors algorithm
Published 2019“…For classification, KNN used before and after enhancement technique based on essential vector with our dataset, the diacritic accuracy was 96.4286% after enhancement, which is better than the 87.5020% in detecting. …”
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Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm
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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image
Published 2016“…The classification accuracy using spectral indices were compared with the normal supervised pixel-based classification of SVM. …”
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Thesis -
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms
Published 2022“…However, there are times where the produce of stray gassing event might lead to fault indication in the transformer. Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. …”
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Online handwritten signature recognition by length normalization using up-sampling and down-sampling
Published 2015“…In this paper, we introduce an efficient algorithm for online signature length normalization by using Up-Sampling and Down-Sampling techniques. …”
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