Search Results - (( data classification means algorithm ) OR ( code classification techniques algorithm ))
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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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Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The retrieval of surface reflectance is important to obtain the atmospheric reflectance in remotely sensed data and later used for algorithm calibration. In this study, two techniques were used to retrieve the surface reflectance, dark target technique and A TCOR2 technique. …”
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A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
Published 2016“…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks
Published 2023“…The accuracy of 2D tumor detection and segmentation are increased, enabling more 3D detection, and achieving a mean classification accuracy of 98 across system records. …”
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum
Published 2023“…Then, the selection of the critical features is chosen via Neural Network (NN) as classification algorithm and Genetic Algorithm (GA) as an optimization technique. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…However, only supervised learning techniques have proofed insufficient for malware classification task. …”
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Proceeding Paper -
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Clustering is one of the means in data mining of predicting the class based on separating the data categories from similar features. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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11
Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms
Published 2016“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2023Article -
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An improved data classification framework based on fractional particle swarm optimization
Published 2019“…Furthermore, the proposed MOFPSO algorithm is hybridized with Back-Propagation (BP), Elman Recurrent Neural Networks (RNN) and Levenberg-Marquardt (LM) Artificial Neural Networks (ANNs) to propose an enhanced data classification framework, especially for data classification applications. …”
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Effective k-Means Clustering in Greedy Prepruned Tree-based Classification for Obstructive Sleep Apnea
Published 2022“…GPrTC algorithm showed better classification accuracies than k-means clustering in almost all the assigned datasets. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Image retrieval of motifs in malay vernacular architecture / Puteri Nor Hashimah M. A. Rahman, Mohd Sabrizaa Abd. Rashid and Baharum Baharudin
Published 2012“…The algorithm will further classify the motifs into two main codes, i.e, Bunga' code and 'Daun' code. …”
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Conference or Workshop Item -
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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Citation Index Journal -
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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