Search Results - (( network implementation using algorithm ) OR ( based classification using algorithm ))
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1
Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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Thesis -
2
An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks
Published 2020“…Due to the non-stationary nature of the ECG signal, it is rather challenging to use traditional handcraft methods, such as time-based analysis of feature extraction and classification, to pave the way for machine learning implementation. …”
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Article -
3
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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4
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…This proposed classifier achieved 97.9% classification accuracy on the ISIC dataset. In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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5
Case Slicing Technique for Feature Selection
Published 2004“…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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6
Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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Conference or Workshop Item -
7
Application Of Neural Network In Malaria Parasites Classification
Published 2006“…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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Monograph -
8
Implementation of machine learning algorithm in preventing network congestion
Published 2023text::Final Year Project -
9
Classification of left/right hand movement from EEG signal by intelligent algorithms
Published 2015“…Principal component Analysis (PCA) has been used for feature reduction. Measured data revealed that the maximum classification accuracy of 84.17 on PCA implemented reduce feature set has been achieved using SOM based classifier. …”
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10
Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / Mohamad Firdaus Mohamad Salehuddin
Published 2020“…This project is about using the Levenberg Marquardt algorithm in Artificial Neural Network (ANN) to classified between clean and polluted water. …”
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Student Project -
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Rabbit breed classification using CNN / Aishah Nabila Mohd Zaid
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Thesis -
12
VHDL modeling of EMG signal classification using artificial neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been used for the classification of EMG signals. …”
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13
Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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14
Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework
Published 2011“…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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15
Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan
Published 2024“…The study's outcomes underscore the capability of the BPNN-based algorithm to attain remarkable accuracy in Songket pattern classification, thus showcasing its viability for real-world applications.…”
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16
Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. For the ANN, Multilayer feed-forward networks are trained using Back Propagation (BP) learning algorithm and for the KNN, is used the most common distance which is Euclidean. …”
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17
Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…Multi-layer perceptron (MLP) neural network is one of the most widely used neural network architecture. …”
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18
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In this paper, object detection model is developed and implemented with deep learning algorithm. Object classification model is produced through the model training with Deep Neural Networks (DNN). …”
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Proceedings -
19
Review of the machine learning methods in the classification of phishing attack
Published 2019“…This study focused on an algorithm that was thoroughly made and the methods in implementing this algorithm are discussed in detail.…”
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An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
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