Implemented K-Means, DBSCAN and Meanshift clustering algorithms on both CPU (using C++) and GPU (using CUDA) as part of CSE560 - GPU Computing course. Also compared the CPU and GPU code using various ...

Co-clustering algorithms and models represent a robust framework for the simultaneous partitioning of the rows and columns in a data matrix. This dual clustering approach, often termed block ...

ABSTRACT: Breast cancer remains one of the most prevalent diseases that affect women worldwide. Making an early and accurate diagnosis is essential for effective treatment. Machine learning (ML) ...

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Abstract: This paper presents the results of some partitional clustering algorithms applied to the segmentation of color images in the RGB space. As more information is involved in the algorithm, and ...

Abstract: Clustering is an important research topic in data mining that appears in a wide range of unsupervised classification applications. Partitional clustering algorithms such as the k-means ...