Search Results - (( rate estimation learning algorithms ) OR ( _ classification based algorithm ))*

Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

“…The performance of ERS algorithm is evaluated based on the classification performance metrics by using classification rate (CR), error rate (ERT), precision (Prec.) and recall (rec.) as well as the number of extremal regions produced by ERS. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

“…The performance of ERS algorithm is evaluated based on the classification performance metrics by using classification rate (CR), error rate (ERT), precision (Prec.) and recall (rec.) as well as the number of extremal regions produced by ERS. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Unfortunately, these algorithms suffer with several drawbacks such as the tendency to be trapped or stagnate into local optima and slow convergence rates. …”
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Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyperparameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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Systematic review and meta-analysis on the classification metrics of machine learning algorithm based radiomics in hepatocellular carcinoma diagnosis by Mohd Haniff, Nurin Syazwina, Ng, Kwan Hoong, Kamal, Izdihar, Mohd Zain, Norhayati, Abdul Karim, Muhammad Khalis

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Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli by Rosli, Mohamed Syazwan Asyraf

“…The Adaptive Moment Estimation (Adam) optimizer and Learning Rate on Plateau are employed to optimize the model's training regime. …”
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". …”
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Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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Hand Gesture Recognition Using Artificial Neural Networks by Mustafa, Mohd Amrallah

“…In order to have a system that can be easily trained, artificial neural networks has been chosen in the classification stage. A multilayer perceptron with back-propagation algorithm has been developed, thus the system is actually in-built to be used as a human machine interface. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

A comparative study on aviation arrival delay prediction using machine learning methods by Chew, Pui Ting

“…This research aims to identify the most important features for flight delay prediction, build supervised machine learning algorithms (i.e., logistic regression (LR), random forest (RF) and artificial neural network (ANN)) for predicting flight arrival delay and compare the performances of the methods. …”
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Neural network approach for estimating state of charge of lithium-ion battery using backtracking search algorithm by Hannan M.A., Lipu M.S.H., Hussain A., Saad M.H., Ayob A.

An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks by Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Ali Farzamnia, Teo, Kenneth Tze Kin, Saeid Sanei

“…To implement the ILMS algorithm, each node needs to receive the local estimate of the previous node on the cycle path to update its own local estimate. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Jaafar, Jafreezal

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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