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Search results for: cluster
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Year: 2020, Volume: 20, Number: 3
... , and Region Growing algorithms for the prediction. The k-Means algorithm was applied to cluster I. INTRODUCTION the MRI images. From the clustered images, the white ... Alzheimer's disease is a most quickly developing disorder grey matter were extracted using the region Growing in older people, which generally starts slowly and affects the algorithm. With ...
Year: 2020, Volume: 20, Number: 3
... y (t) ïƒ (1) cosmology, Brownian motions are also used to study   0 if x(t)  T galaxies, galaxy clusters, and voids [13]. A non-linear where T is a threshold determined experimentally. The bistable system is one of the typical SR models. Its ...
... procedure reduces the data dimensionality, remove is the k-means clustering algorithm [34-35]. There are redundant or ... filter resulted in further improvement on the visibility of the clusters of microcalcifications, allowing a detailed study of their ... detection of Zwiggelaar. "Topological Modeling and Classification of clustered microcalcifications in digital mammograms using Mammographic Microcalcification Clusters" ...
Year: 2019, Volume: 19, Number: 4
... . 1255-1260, 2014. doi:10.3969/j.issn.1002- 0802.2014.11.004. [4] A. Swami and B. Sadler, "Modulation classification via hierarchical agglomerative cluster analysis," In First IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications, pp. 141-144, 1997. doi:10.1109/spawc.1997.630180. ...
Year: 2019, Volume: 19, Number: 4
... problem depending on processing technologies, using new methods such as neural power system data. PF becomes more complicated due to networks; deep learning; heuristic methods and clustering system constraints whereas satisfying the system based optimization techniques in order to solve power flow parameters. Power system operating is a challenging task has grown, rapidly. ...
Year: 2019, Volume: 19, Number: 4
... this cascading can be repeated depending on the speed up the convergence rate recently [29]. For data number of transmission lines used in the design, which clustering improved hybrid method based on cuckoo means the general formula can be extended as: optimization and modified particle swarm optimization was suggested by Bouyer and Hatamlou [30 ...
Year: 2019, Volume: 19, Number: 4
... F. Pla, J. M. Sotoca, P. GarcÃa-Sevilla, "Clustering- Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel ... selection. and spectral information of a band combination using a Some examples are a clustering-based method developed minimum number of bands [12]. Another method is the ...
58. Comparison of Classification Algorithms for Detecting Patient Posture in Expandable Tumor Prostheses
Year: 2020, Volume: 20, Number: 2
... – 1182, 2003. [36] S. Halkiotis, T. Botsis, M. Rangoussi. "Automatic detection of doi:10.1016/j.aca.2011.07.027. clustered microcalcifications in digital mammograms using [51] Y. W. Chen, C. J. Lin, "Combining SVMs with various feature mathematical morphology and ...
59. Generation of Visual Patterns from BoVW for Image Retrieval using modified Similarity Score Fusion
Year: 2020, Volume: 20, Number: 2
... In [22], in order to support for large-scale database and lacks to provide spatial information [9-11], thereby, images, random forest predictive tree clustering is applied to causes false positive matches and reduces its precision construct vocabulary and thus, improves the discriminative ability among the images. Digital Object Identifier 10.4316/ ...
Year: 2020, Volume: 20, Number: 2
... . above dataset where four different methods are compared including the approach by Pape and Klukas [11]. In I. INTRODUCTION Nottingham method, Simple Linear Iterative Clustering (SLIC) superpixels based technique is applied in Lab color As agriculture is emerging as an important technology space to segment the image from the background. Centroids ...
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