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58 results for “k-means clustering algorithm”
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Research ArticleOpen accessIn the abstractPolar Disentangled Non-Local Convolutional Neural Network for Skin Cancer Classification Using Dermoscopy ImagesUsha Thirugnanam, Nalini JosephSkin cancer classification is the process of identifying and categorizing various types of skin lesions into cancerous and non-cancerous. This process is performed to achieve accurate detection, which minimizes the risk of severe health complications. However, classifying the severity of skin lesion images is a difficult task because of subtle and overlapping visual patterns, which could lead to inaccurate performance. … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Clustering Robustness through Fuzzy Ensemble of K-Means and Mean ShiftLNC. Prakash K., Palamakula Ramesh Babu, Shaik Thaseentaj et al.Ensemble clustering has emerged as a powerful strategy to improve the robustness and accuracy of unsupervised learning, particularly when individual algorithms struggle with noisy, heterogeneous, or high-dimensional data. This study introduces a fuzzy-based ensemble approach that integrates the complementary strengths of K-Means and Mean Shift clustering, followed by fuzzy membership assignment for data points that remain ambiguous. The inclusion of … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,257 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Detailed Preserving Medical Image Denoising Using Cluster-Wise PCA Thresholding and Iterative Mean FilteringMohit Sharma, Ayush Dogra, Anita Gupta et al.Image denoising is a vital process in medical imaging that involves removing noise or distortions introduced during image acquisition. Random noise can degrade image quality and reduce contrast, making accurate analysis more challenging. This paper presents a detail-preserving medical image denoising framework based on a hybrid methodology that combines cluster-wise Principal Component Analysis (PCA) thresholding with Iterative Mean Filtering (IMF). … …Journal of Computer Science, Vol. 22, Issue 4 · 18 Apr 2026 · 1,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetecting Anomalies in IoT Using Intuitionistic Fuzzy Clustering AlgorithmsVijo Arul Selvi M., Fehmin Nadira Laskar, Fokrul Alom Mazarbhuiya et al.Intuitionistic Fuzzy Sets (IFS) are convenient ways to represent the vagueness and uncertainty inherent in any dataset. There are many uses of these. One such use is the Fuzzy C-Means (FCM) algorithm, which clusters the data objects into a pre-assigned (c) number of fuzzy clusters, which has been adopted in many fields, namely, pattern classification, anomaly detection, fraud identification, etc. … …Journal of Computer Science, Vol. 22, Issue 2 · 2 Mar 2026 · 1,600 accessesView PDFCite
Research ArticleOpen accessIn the abstractIncorporation of Modified Region Growing into FCM Clustering for Extraction of Tumors in MR ImagesLovepreet Singh Brar, Jaget Singh, Bhawana Agrawal et al.Due to the tremendous growth of medical Magnetic Resonance (MR) images, it becomes an essential requirement for an automated extraction of diagnostically salient parts of the images to refine the transmission and storage process. Research method: This paper proposes an automated unsupervised machine learning segmentation technique named fuzzy c-means clustering based on modified region growing algorithm (RG-FCM) for the extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Customer Predictive Model for Investment Using Ensemble Learning TechniqueThongchai Kaewkiriya, Kittipol WisaengMany new investors that want to purchase a fund might be disappointed with the return-on-investment value. This problem occurs because they do not know important factors that could affect the market value. Plus, some assets might not be suitable for the investor's investment style. To reduce the mentioned problems, many asset management companies research the systems that could find a … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,472 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Study on Emotion Analysis and Music Recommendation Using Transfer LearningKrishna Kumar Singh, Payal DemblaAs more and more people access and consume music through streaming platforms and digital services, music recommendation has grown in importance within the music industry. Given the abundance of music at our disposal, music recommendation algorithms are essential for guiding users toward new music and for creating individualized listening experiences. People frequently seek out music that fits their current emotional … …Journal of Computer Science, Vol. 19, Issue 6 · 16 May 2023 · 7,109 accessesView PDFCite
Research ArticleOpen accessIn the abstractGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeometrical Approach to a New Hybrid Grid-Based Gravitational Clustering AlgorithmFaisal Bin Al Abid, A.N.M. Rezaul Karim, Golam Rahman ChowdhuryIn the past years, several clustering algorithms have been developed, for example, K-means, K-medoid. Most of these algorithms have the common problem of selecting the appropriate number of clusters and these algorithms are sensitive to noisy data and would cause less accurate clustering of the data set. Therefore, this paper introduces a new Hybrid Grid-based Gravitational Clustering Algorithm (HGGCA) geometrically, … …Journal of Computer Science, Vol. 17, Issue 3 · 9 Mar 2021 · 6,783 accessesView PDFCite