Search Results - (( quality classification based algorithm ) OR ( data visualization using algorithm ))
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1
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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2
A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
Published 2016“…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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3
Classification and visualization: Twitter sentiment analysis of Malaysia’s private hospitals
Published 2023“…Term frequency-inverse document frequency is used for text mining, information retrieval techniques, and the Naïve Bayes, a machine learning algorithm for the classification. …”
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4
A novel lip geometry approach for audio-visual speech recognition
Published 2014“…First, this work presents a new method to extract lip geometry features using the combination ofa skin colour filter, a border following algorithm and a convex hull approach. …”
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5
Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials
Published 2013“…(ii) Multiresolution signal decomposition technique is then applied to reduce the dimensionality of the data. (iii) The image ofthe defect region is reconstructed by using the attenuation of the reflected ultrasound signal (iv) Entropy-based fuzzy k-nearest neighbour classification method is used to extract the feature of the defects. …”
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6
Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…Targeting on impulse noise density as high as 50%, 60%, 70%, 80% and 90%, the model has been trained with a massive collection of natural images and 14 standard testing images are used for validation purposes. Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
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7
Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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8
A stable and accurate wavelet-based method for noise reduction from hyperspectral vegetation spectrum
Published 2015“…SLWT incorporates the advantages of both SWT and LWT methods, including a translation invariance property and a fast simple algorithm. Experimental results show that SLWT highly outperforms other wavelet-based methods in terms of accuracy and visual quality. …”
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9
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…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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10
Classification model for water quality using machine learning techniques
Published 2015“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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11
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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12
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distribution. …”
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13
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…Confusion matrix analysis confirmed the robustness of the LM-based classifier across varying input data ratios. …”
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14
Aco-based feature selection algorithm for classification
Published 2022“…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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15
Development Of An Intelligent System For River Water Quality Classification Based On Algae Composition
Published 2006“…Throughout the years, many researches have been conducted on the potential applications of Artificial Intelligence (AI) in the biological monitoring of river quality. This project will provide an overview regarding the feasibility of the application of neural networks for direct classification of river water quality based on algae composition. …”
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16
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Classification rules were generated based on the best reduct. …”
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17
The Development Of System For Algorithms Visualization Using Simjava
Published 2020“…Algorithms are a captivating use case for visualization. …”
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18
Power quality problem classification based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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19
Improved building roof type classification using correlation-based feature selection and gain ratio algorithms
Published 2017“…Then, the quality of the selected features was assessed using correlation-based feature selection (CFS). …”
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20
A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method
Published 2011“…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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