Search Results - (( parallel classification techniques algorithm ) OR ( code classification matching algorithm ))
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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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“…For next, instead of k-means clustring, Fuzzy cmeans clustering is combined with Spatial Pyramid Matching image representation to improve the accuracy of classification results. …”
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Text classification using Naive Bayes: An experiment to conference paper
Published 2005“…The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. …”
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…For sentiment detection, the AOADL-TC technique applies a parallel bidirectional gated recurrent unit (BiGRU) model. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Sensitivity Encoding (SENSE) is a widely used technique to reconstruct the artefact free images from the Parallel MRI (pMRI) aliased data. …”
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets
Published 2025“…To accommodate big-scale data, the method integrates a parallel computing framework, Dask, during both the reduction and classification processes. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Development of a parallel clustering of bilingual corpora based on reduced terms
Published 2015“…It helps in verifying the classification and constraints of languages. Other than that, it also helps in eliminating the biased language-specific usages. …”
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Robust partitioning and indexing for iris biometric database based on local features
Published 2018“…Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. …”
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Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors
Published 2016“…Over the past few years, various finger vein recognition algorithms and techniques have been proposed by researchers and scholars. …”
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
Published 2016“…The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. The experimental results showed that the recognition rate achieved are of 99.9% on Bath-A data set, with a maximum decision criterion of 0.97.…”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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