Search Results - (( parameter implementation using algorithm ) OR ( level classification using algorithm ))
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1
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Several methods have been used to classify the ASD from non-ASD people. However, there is a need to explore more algorithms that can yield better classification performance. …”
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2
Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…The basic feature extraction of minimum, maximum and mean of gray level values are used as the parameter to develop the prototype. …”
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Thesis -
3
Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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4
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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5
Power quality problem classification based on Wavelet Transform and a Rule-Based method
Published 2010“…Since the method can reduce the number of parameters needed in classification, less memory space and computing time are required for its implementation. …”
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6
Detection of corneal arcus using rubber sheet and machine learning methods
Published 2019“…The elements extracted from the confusion matrix parameters (i.e. accuracy, specificity, sensitivity, AUC, precision and f-score) are used in benchmarking the optimal performance of classification algorithms. …”
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7
Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…Since the method can reduce the number of parameters needed in classification, less memory space and computing time are required for its implementation. …”
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8
Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…Since the method can reduce the number of parameters needed in classification, less memory space and computing time are required for its implementation. …”
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9
Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…These rule sets was implemented in the MYEmotion using MATLAB environment. …”
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10
Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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11
Development of gender and race recognition system using speech and recognition by using frequency spectrum
Published 2009“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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Learning Object -
12
Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…However, despite the large number of studies on the analysis of mental health disorders, the predominant algorithm in the existing literature is the Multi-Class Single-Level (MCSL) classification algorithm, which is often used for simple classification tasks involving a limited number of classes. …”
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13
Symmetric Key Size for Different Level of Information Classification
Published 2006“…Therefore confidential information is normally protected by using cryptographic algorithms. In these algorithms, key is an important element since it is one of the parameters that determine the level of security that the algorithms can provide. …”
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14
Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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Book Section -
15
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…Feature extraction for oil palm FFB colour, texture, and thorns was implemented by using statistical colour features, colour histogram, grey-level co-occurrence matrices (GLCM), basic grey level aura matrix technique (BGLAM), and Gabor wavelet techniques on the three different regions of interest (ROIs), namely, ROI1, ROI2, and ROI3. …”
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16
Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper -
17
Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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18
Automatic classification of medical x-ray images
Published 2013“…Experimental results showed the classification performance obtained by exploiting LBP and BoW outperformed the other algorithms with respect to the image representation techniques used.…”
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19
Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm
Published 2021“…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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20
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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