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A survey on the utilization of Superpixel image for clustering based image segmentation
Superpixel become increasingly popular in image segmentation field as it greatly helps
image segmentation techniques to segment the region of interest accurately in noisy …
image segmentation techniques to segment the region of interest accurately in noisy …
[PDF][PDF] Exploring Big Data Clustering Algorithms for Internet of Things Applications.
With the rapid development of the Big Data and Internet of Things (IoT), Big Data
technologies have emerged as a key data analytics tool in IoT, in which, data clustering …
technologies have emerged as a key data analytics tool in IoT, in which, data clustering …
A Survey and Experimental Review on Data Distribution Strategies for Parallel Spatial Clustering Algorithms
Abstract The advent of Big Data has led to the rapid growth in the usage of parallel
clustering algorithms that work over distributed computing frameworks such as MPI …
clustering algorithms that work over distributed computing frameworks such as MPI …
Indexing in wot to locate indoor things
The Web of Things (WoT) is an enhanced form of the Internet of Things (IoT) that has
changed the trend of life nowadays. Due to IoT, life is transformed into smart life, such as …
changed the trend of life nowadays. Due to IoT, life is transformed into smart life, such as …
Grid-R-tree: A data structure for efficient neighborhood and nearest neighbor queries in data mining
The use of multi-dimensional indexing structures has gained a lot of attention in data mining.
The most commonly used data structures for indexing data are R-tree and its variants, quad …
The most commonly used data structures for indexing data are R-tree and its variants, quad …
Engineering massively parallel MST algorithms
We develop and extensively evaluate highly scalable distributed-memory algorithms for
computing minimum spanning trees (MSTs). At the heart of our solutions is a scalable …
computing minimum spanning trees (MSTs). At the heart of our solutions is a scalable …
Anytime clustering of data streams while handling noise and concept drift
Clustering of data streams has become very popular in recent times, owing to rapid rise of
real-time streaming utilities that produce large amounts of data at varying inter-arrival rates …
real-time streaming utilities that produce large amounts of data at varying inter-arrival rates …
Implementing scalable machine learning algorithms for mining big data: a state-of-the-art survey
The growing trend of Big Data drives additional demand for novel solutions and specifically-
designed algorithms that will perform efficient Big Data filtering and processing, recently …
designed algorithms that will perform efficient Big Data filtering and processing, recently …
A research roadmap of big data clustering algorithms for future internet of things
Due to the massive data increase in different Internet of Things (IoT) domains such as
healthcare IoT and Smart City IoT, Big Data technologies have been emerged as critical …
healthcare IoT and Smart City IoT, Big Data technologies have been emerged as critical …
An empirical review on data feature selection and big data clustering
VR Maddumala, R Arunkumar, S Arivalagan - Asian Journal of Computer …, 2018 - ajcst.co
With the fast advancement of the Big Data, Big Data innovations have risen as a key data
investigation apparatus, in which, feature extraction and data bunching calculations are …
investigation apparatus, in which, feature extraction and data bunching calculations are …