Search Results - (( data segmentation model algorithm ) OR ( java implication based algorithm ))

Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

“…Rapid growth of multimedia data in cyberspace caused a swift rise in data transmission volume. …”
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Segmentation of MRI Prostate Images using Gaussian Mixture Models (GMMs) by Roslee, Nur Aqilah

“…In this paper, the performance of Gaussian Mixture Model method for medical image segmentation is assessed with the help of Expectation-Maximization (EM) method for data training and Bayesian Information Criterion (BIC) function to prevent data overfitting. …”
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso by Mohammed Adam Kunna, Azrag, Jasni Mohamad, Zain, Tuty Asmawaty, Abdul Kadir, Marina, Yusoff, Jaber, Aqeel Sakhy, Abdlrhman, Hybat Salih Mohamed, Ahmed, Yasmeen Hafiz Zaki, Husain, Mohamed Saad Bala

“…The numerical findings indicate a good agreement between the observed and predicted data. In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting by Mansor, R., Kasim, M.M., Othman, M.

“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of three main phases; data pre-processing, forecasting based on WeSuSFTS model and model evaluation. …”
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Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

“…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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Determination of tree height based on tree crown using algorithm derived from UAV imagery / Suzanah Abdullah ... [et al.] by Abdullah, Suzanah, Tahar, Khairul Nizam, Abdul Rashid, Mohd Fadzil, Osoman, Muhammad Ariffin

“…The single tree crown was obtained from the digital surface model by using four algorithms such as watershed segmentation, object based image analysis, inverse watershed segmentation and seed generation. …”
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M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Customer segmentation using clustering techniques / Mohamad Amir Salihin Mustafa by Mustafa, Mohamad Amir Salihin

“…This study explores clustering techniques for customer segmentation, focusing on the K-Means algorithm in particular, and uses a dataset that was obtained from the customer data of an international supermarket company. …”
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A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI by Rafi, A., Khan, Z., Aslam, F., Jawed, S., Shafique, A., Ali, H.

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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…Semantic segmentation annotation helps train computer vision based Artificial Intelligence models where each image pixel is assigned to a specific object class. …”
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An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

“…Further works that can be explored in this area include adopting a robust preprocessing strategy to increase data variability and improve model generalization or implementing an optimizationenhanced strategy on the existing segmentation models for comparison.…”
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Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

“…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid by Khalid, Nurul Syafiqah

“…Lastly, to compare the accuracy assessment of watershed transformation segmentation and local maxima algorithm. The data used is Pleiades high spatial resolution satellite imagery and LiDAR data. …”
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Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model by Azrag, Mohammed Adam Kunna, Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

“…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling by Muhammad Ismaill, Mat Lizah, Nasrul Hadi, Johari, Mohd Jamil, Mohamed Mokhtarudin

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Malay continuous speech recognition using continuous density hidden Markov model by Ting, Chee Ming

“…HMM is a robust and powerful technique capable of modeling of speech signals. With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

“…The high accuracy performance shows potential for the models to be employed for collision avoidance algorithm in ASV navigation.…”
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