Search Results - (( variable visualization using algorithm ) OR ( lesion classification using algorithm ))
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Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)
Published 2015“…Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. …”
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Novel techniques for enhancement and segmentation of acne vulgaris lesions
Published 2013“…Conclusion: This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions.…”
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Citation Index Journal -
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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Automated Segmentation And Classification Technique For Brain Stroke
Published 2019“…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features
Published 2018“…After which, the extracted features were subjected to particle swarm optimization (PSO) technique for the selection of a set of optimized features for classification. Our automated CAD system can differentiate normal, malignant, and benign liver lesions using machine learning algorithms. …”
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Ensemble learning of deep learning and traditional machine learning approaches for skin lesion segmentation and classification
Published 2022“…After that segmented region is classified into three types of skin lesion using hybrid features of Alex-Net and VGG-16 through the transfer learning approach. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…This research is divided into two phases – 1) Feature Engineering phase explains skin conditions based on lesion segmentation and different dermoscopic feature extraction, while 2) Classification phase detects Melanoma. …”
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Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi
Published 2004“…RGB colour variegations are useful features used by the domain's experts in their morphological learning method for skin disease classification. …”
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Research Reports -
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An efficient AdaBoost algorithm for enhancing skin cancer detection and classification
Published 2024“…To improve accuracy, the AdaBoost algorithm is utilized, which amalgamates weak classification models into a robust classifier with high accuracy. …”
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Automated Detection and Classification of Retinal Vein Occlusion Using Ultra-widefield Retinal Fundus Images and Transfer Learning
Published 2024“…The study also evaluates the classification model trained with lesion masks to classify images accurately into the respective categories. …”
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Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…This study describes application of a hybrid combination of hybrid evolutionary algorithm (HEA) and thematic map visualization technique in modeling, predicting and visualization of selected algae division growth, Chlorophyta for tropical Putrajaya Lakes and Wetlands (Malaysia). …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images
Published 2025“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…It assists design engineers as it gives a clearer visualization to predict which value of the variables gives a best produced result. …”
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Final Year Project -
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…Particularly, this thesis aims to (1) minimize the interaction level of the computer-aided procedure, (2) visualize the arteries without obstruction and (3) detect the stenosis with consistent observation using the computer-aided procedure. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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KNN Algorithm to Determine Optimum Agricultural Commodities in Smart Farming
Published 2023“…The algorithm used in this research is KNN, which was chosen because the variable has a numeric data type to perform the matching. …”
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