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25 articles for “partitioning algorithm”
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Image Segmentation based on Region Merging using Breadth-First Search
Abstract: This paper proposed a new method for image segmentation based on region merging using breadth-first search (BFS). The image can be partitioned into multiple segments so that meaningful information is extracted out and then image is analyzed easily. In the proposed method, first the oversegmented image is obtained by applying a standard watershed transformation on original image. Then BFS is executed on the oversegmented image to obtain a segmented image. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 20–25 Read article
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A Survey of Edge Detection and Object Segmentation from Contour based Soft Computing Approaches
Abstract: Soft computing approaches such as consisting of fuzzy logic, neural or evolutionary computation are the emerging field with the wide applications in edge detection and image segmentation. Such a process of partitioning the pixels regions of the digital images with boundary between two homogenous regions refers to the detection of edges. There was various approaches that have been implemented to achieve the same but their performance and its scope of …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 1, 2015 · pp. 16–20 Read article
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Advances in Data Security in Cryptography
Abstract: In the ultra-modern period, evaluation of networking and wireless networks within information and communication technology has brought many changes to deal with this technology using internet, growing strongly over the past several decades, data security has come a main concern for anyone connected to the web. Data security ensures that our data can only be accessed by authorized recipients and prevents any unauthorized access or alteration of the data. We …
Published in Journal Of Network security · Vol. 12, Issue 1, 2024 · pp. 1–7 Read article
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A Novel Clustering Techniques Evaluation using Monte Carlo Simulation
Abstract: In Machine Learning clustering is one the most significant method. Today, we have data in rich from many sources but in order to get meaningful information from it is very boring task. Machine learning clustering algorithms to create cluster to decode the meaningful information from the data, this analysis approach has gained much popularity in recent years. This paper explores evaluation performance of frequently used existing clustering techniques such as …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 1–23 Read article
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Challenges in Parallel Computing for Big Data Analytics
Abstract: The integration of parallel computing into the realm of big data analytics promises accelerated processing speeds and enhanced scalability, but it is not without its formidable challenges. This study explores the multifaceted hurdles faced in the pursuit of efficient parallel processing for large-scale data analytics. The intricate task of distributing and partitioning massive datasets across multiple processing units demands adept strategies to ensure equitable workloads. Load balancing emerges as a …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article