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1
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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2
Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…The constrained layer enables the CNN model to learn the required features directly from ubiquitous image input and then performs classification. …”
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Thesis -
3
Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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4
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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5
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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6
Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
7
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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8
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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9
Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Final Year Project -
10
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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11
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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12
Waste management using machine learning and deep learning algorithms
Published 2020“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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13
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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14
An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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An automated strabismus classification using machine learning algorithm for binocular vision management system
Published 2023“…To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. …”
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Proceeding Paper -
17
Performance comparison of CNN and LSTM algorithms for arrhythmia classification
Published 2020“…Among the existing deep learning model, convolutional neural network (CNN) and long short-term memory (LSTM) algorithms are extensively used for arrhythmia classification. …”
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18
A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification
Published 2024“…For machine learning, SVM is a very good classification model. …”
Conference Paper -
19
Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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20
Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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