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41 results for “Supervised Classification”
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Research ArticleOpen accessIn the abstractRetinal Image Analysis for Abnormality Detection-An OverviewR. Karthikeyan, P. AlliProblem statement: Classification plays a major role in retinal image analysis for detecting the various abnormalities in retinal images. Classification refers to one of the mining concepts using supervised or unsupervised learning techniques. Approach: Diabetic retinopathy is one of the common complications of diabetes. Unfortunately, in many cases, the patient is not aware any symptoms until it is too late … …Journal of Computer Science, Vol. 8, Issue 3 · 24 Jan 2012 · 7,280 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Classification of Cancer using Support Vector Machines and Modified Extreme Learning Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The primary objective is to propose efficient cancer classification techniques which provide reliable and significant classification accuracy. To achieve this primary research goal is to find the smallest set of genes that can ensure high accuracy in classification using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: (a) The computational burden and … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 7,441 accessesView PDFCite
Research ArticleOpen accessIn the abstractCancer Classification using Support Vector Machines and Relevance Vector Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The objective of this study is, to find the smallest set of genes that can ensure highly accurate classification of cancer from micro array data by using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: The computational burden and noise arising from irrelevant genes are much reduced; the cost for cancer testing … …Journal of Computer Science, Vol. 7, Issue 9 · 25 Jul 2011 · 7,593 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study in Classification Techniques for Unsupervised Record Linkage ModelMohammadreza Ektefa, Fatimah Sidi, Hamidah Ibrahim et al.Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 8,199 accessesView PDFCite
Research ArticleOpen accessIn the abstractSummarizing Relational Data Using Semi-Supervised Genetic Algorithm-Based Clustering TechniquesRayner AlfredProblem statement: In solving a classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, we may loss some information when we join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,585 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew Constructive Neural Network Architecture for Pattern ClassificationS. S. Sridhar, M. PonnavaikkoProblem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,565 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordA Systematic Review of Adversarial Attacks: ML Techniques, Classification and CountermeasuresBhavesh Kumar Sharma, Sanatan Ratna, Rajiv KumarMachine Learning (ML) and Deep Learning (DL)-based technologies have made significant strides in areas such as computer vision, natural language processing, and autonomous systems. Yet they have been applied in high-stake applications, and have been found to be fragile through adversarial attacks-, maliciously crafted small distortions that fool models into making mistakes. From the pioneering work by Szegedy et al. … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,497 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEvaluation of Transfer Learning for Mask DetectionZahin Akram, Arifuzzaman Arman, Mohammad Rakib Imtiaz, Syed Athar Bin AmirThe use of masks has become crucial in combating the Coronavirus pandemic. Unfortunately, the regulation of wearing a mask is not being upheld by many citizens which is contributing to the spread of the disease. To aid the efforts of regulations and to maintain safety in public areas, both large like parks or small like public transport, Artificial Intelligent systems … …Journal of Computer Science, Vol. 18, Issue 2 · 3 Mar 2022 · 6,931 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordWord Sense Disambiguation: Survey StudyAhmed H. Aliwy, Hawraa A. TaherThe process of identifying the correct sense of a given word in a particular sentence is called Word Sense Disambiguation (WSD). It is complex problem because it involves drawing knowledge from various sources. Significant amount of effort has been put into resolving this problem in machine learning since its inception but the toil is still ongoing. Many techniques were used … …Journal of Computer Science, Vol. 15, Issue 7 · 26 Jul 2019 · 8,388 accessesView PDFCite