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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population
Published 2023“…It gives 97.75% of mean precision, 93.95% of mean sensitivity and 95.7% of mean specificity. …”
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Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition
Published 2022“…This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…The Fuzzy c-means clustering improved the accuracy of classification task to 40.53%. …”
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Fuzzy voice classifier and fuzzy voice pathology identification system
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Hybrid intelligent approach for network intrusion detection
Published 2015“…Clustering is the last step of processing before classification has been performed, using k-means algorithm. …”
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Monitoring Land Cover Changes in Halabja City, Iraq.
Published 2013“…All images are rectified and registered to Universal Transverse Mercator (UTM), zone 38N and WGS_84 datum. Hybrid classification as a combine of k-Means and Maximum Likelihood Classification (MLC) algorithms were applied to classify the images in five different land cover categories: water body, cultivated area, shrub land, urban area and bare land. …”
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Classification for Quran authentication using characters and diacritics hashed values
Published 2024journal::journal article -
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Consequently, optimization algorithms including binary gravitation search algorithm (BGSA) and binary particle swarm optimization (BPSO), were employed to identify the optimal channels for gender classification. …”
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Students Activity Recognition By Heart Rate Monitoring In Classroom Using K-means Classification
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Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing
Published 2022“…Firstly, the extracted features are classified by the k-means method to demonstrate the classification of self-stimulatory behaviours in a completely unsupervised way. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Adaptive resonance theory-based hand movement classification for myoelectric control system
Published 2014“…First evaluation considers the investigation of feature extraction method; where the proposed multi-feature consisting of Mean Absolute Value (MAV), Zero Crossing (ZC), Waveform Length (WL), Slope Sign Change (SSC), Root Mean Square (RMS), and Mean Frequency (MNF) has been compared to 2 well-known high accuracy and simple multi-feature methods. …”
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A Multi-Criteria Decision-Making Approach for Targeted Distribution of Smart Indonesia Card (KIP) Scholarships
Published 2025“…Third, the classification of scholarship recipient eligibility was performed by comparing the C5.0 and K-Nearest Neighbors (KNN) algorithms. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…The study’s findings indicate that the proposed method improves classification performance for patterns with mean changes of less than 1.5 sigma, and confirm that the performance of the ensemble classifier is superior to that of the individual classifier. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…The study’s findings indicate that the proposed method improves classification performance for patterns with mean changes of less than 1.5 sigma, and confirm that the performance of the ensemble classifier is superior to that of the individual classifier. …”
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