Search Results - (( lesion classification using algorithm ) OR ( code classification methods 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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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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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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Chain coding and pre processing stages of handwritten character image file
Published 2010“…Each of the pre-processing stages and the chain coding process will be described in detail giving improvised algorithms, and examples of the processes on existing samples from the database shown. …”
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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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Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
Published 2023“…With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. …”
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Conference or Workshop Item -
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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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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…The hybrid method was exemplified in a binary classification between digits ‘4’ and ‘9’ from a multiple features dataset. …”
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