Search Results - (( basic classifications using algorithm ) OR ( using application based algorithm ))
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1
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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Conference or Workshop Item -
2
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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Thesis -
3
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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4
Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…Once the image of a target is captured digitally, a myriad of image processing algorithms can be used to extract features from it. …”
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5
Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework
Published 2011“…Once the image of a target is captured digitally, a myriad of image processing algorithms can be used to extract features from it. …”
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6
Neural network paradigm for classification of defects on PCB
Published 2003“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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7
Review of Wheat Disease Classification and Severity Detection Models
Published 2023“…This paper mainly aims to explain deep learning-based wheat diseases identification algorithm, and to discuss the benefits and drawbacks of present wheat disease detection approaches. …”
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8
A Novel Method for Fashion Clothing Image Classification Based on Deep Learning
Published 2023“…Image recognition and classification is a significant research topic in computational vision and widely used computer technology. …”
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9
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…To reduce the misclassification, a feature selection algorithm (using information gain and principal component analysis schemes) is developed to elicit the most discriminative feature subset. …”
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10
Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Neural Networks (NNs) are one of the most popular techniques to perform non-linear classification, and have been extensively used in the literature to perform intrusion detection. …”
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11
Modelling of clinical risk groups (CRGs) classification using FAM
Published 2006“…FAM is a fast learning algorithm and used less epoch training [4]. Based on its performance in doing the classification, FAM is theoretically suitable to do the CRGs classification. …”
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Conference or Workshop Item -
12
A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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13
EMG motion pattern classification through design and optimization of neural network
Published 2012“…Extracted time and time-frequency based feature sets are used to train the neural network. A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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Proceeding Paper -
14
Disposable Biomimetic Array Sensor Strip Coupled With Chemometric Algorithm For Quality Assessment Of Orthosiphon Stamineus Benth Samples
Published 2006“…A disposable screen printed array sensor strip based on self-plasticized methacrylate acrylate PVC blend lipid membranes combined with chemometric algorithm has been developed and applied for qualitative and quantitative analysis of O.stamineus samples. …”
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15
Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…Factors which impact PCANet are studied to identify the limitations of PCANet. For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. …”
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Monograph -
16
The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. …”
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Simulation on Emotion Recognition for Autism Therapy
Published 2017“…The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
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Final Year Project -
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The basic design for the network is provided together with the learning rules. …”
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20
A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets
Published 2024“…We propose a modified reweighted fast consistent and high breakdown point (MRFCH) estimator to make it applicable to high-dimensional settings. The basic idea of our proposed method is to modify the Mahalanobis distance so that it uses only the diagonal elements of the scatter matrix in the computation of the RFCH algorithm. …”
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