Search Results - (( data normalization based algorithm ) OR ( based classification method algorithm ))
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1
Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. …”
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2
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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3
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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4
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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5
Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data
Published 2011“…As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
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6
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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7
Anomaly behavior detection using flexible packet filtering and support vector machine algorithms
Published 2016“…Furthermore, Network traffic prediction algorithms based on SVM such as EaSVM have commented about the fundamental difficulties in achieving an accurate declaration that defines anomaly which suppose to solve the problem of the high rate of false positive alarm and finding excellent ways that guarantees to clear up pending issues of the network traffic normality such as the alluvial data noise of the TAaM method. …”
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8
Automatic Classification of Cervix Type
Published 2019“…Due to that, in this study, few algorithms were developed by using image classification methods to correctly classify the cervix types based on cervical images by using segmentation and classification method. …”
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9
Quranic diacritic and character segmentation and recognition using flood fill and k-nearest neighbors algorithm
Published 2019“…The diacritic detections are performed using a region-based algorithm with 89% accuracy and 95% improved by using flood fill segmentations method. 2DMED feature extraction accuracy was 90% for diacritics and 96% improved by applied CNN. …”
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10
Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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11
Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image
Published 2016“…Normal supervised pixel-based classification scheme is often applied to map urban land use and land cover which the accuracy is dependent on the training site information. …”
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12
Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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13
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. …”
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14
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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15
EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
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17
Data mining in mobile ECG based biometric identification
Published 2014“…Subjects in MIT-BIH Normal Sinus Rhythm Database (NSRDB) were used to validate the reliability and stability of the subject recognition methods. Discriminatory features extracted from the experimentation were later applied to different classifiers for performance measures based on the complexity of our proposed sample extraction method when compared to other related algorithms, the total execution time (TET) applied on different classifiers in various mobile devices and the classification accuracies when applied to various classification techniques. …”
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18
VGG16-based deep learning architectures for classification of lung sounds into normal, crackles, and wheezes using Gammatonegrams
Published 2023“…Breathing sounds are a rich source of information that can assist doctors in diagnosing pulmonary diseases in a non-invasive manner. Several algorithms can be developed based on these sounds to create an automatic classification system for lung diseases. …”
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19
Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
Published 2013“…K-Means clustering is applied to labeling and gathers the entire data into corresponding cluster sets based on the data behavior, i.e. , i.e. normal and attack, while Naïve Bayes Classifier (NBC) is applied to reorder the misclassified clustered data into correct categories. …”
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20
Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
Published 2013“…,i.e. normal and attack, while Naïve Bayes Classifier (NBC) is applied to reorder the misclassified clustered data into correct categories. …”
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