scholarly journals Analysis of a hybrid fractal curve antenna using the segmentation method

2020 ◽  
Vol 2 (11) ◽  
Author(s):  
Atif Jamil ◽  
Mohd Zuki Yusoff ◽  
Noorhana Yahya
Keyword(s):  
Segmentation Method ◽  
Fractal Curve

Meet fractal curves with 1C:MathKit

2020 ◽  
pp. 38-48
Author(s):  
O. M. Korchazhkina
Keyword(s):  
Methodological Approach ◽  
Fractal Curve ◽  
Iterative Processes ◽  
Geometric Figures ◽  
Modern Natural ◽  
Geometric Objects ◽  
Ict Tools ◽  
Subject Areas ◽  
The Subject ◽  
And Mathematics

The article presents a methodological approach to studying iterative processes in the school course of geometry, by the example of constructing a Koch snowflake fractal curve and calculating a few characteristics of it. The interactive creative environment 1C:MathKit is chosen to visualize the method discussed. By performing repetitive constructions and algebraic calculations using ICT tools, students acquire a steady skill of work with geometric objects of various levels of complexity, comprehend the possibilities of mathematical interpretation of iterative processes in practice, and learn how to understand the dialectical unity between finite and infinite parameters of flat geometric figures. When students are getting familiar with such contradictory concepts and categories, that replenishes their experience of worldview comprehension of the subject areas they study through the concept of “big ideas”. The latter allows them to take a fresh look at the processes in the world around. The article is a matter of interest to schoolteachers of computer science and mathematics, as well as university scholars who teach the course “Concepts of modern natural sciences”.

An Algorithm for Enumerating Intersections of Line Segments Using Space Segmentation Method

2016 ◽  
Vol 136 (12) ◽  
pp. 1683-1690
Author(s):  
Osami Yamamoto ◽  
Kota Ishikawa
Keyword(s):  
Segmentation Method ◽  
Line Segments

Mask R-CNN based segmentation method for satellite imagery of photovoltaics generation systems

2020 ◽  
Author(s):  
SiMing Liang ◽  
FengYang Qi ◽  
YiFan Ding ◽  
Rui Cao ◽  
Qiang Yang ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Segmentation Method

Segmentation In Medical Resonance images to extract the cancerous nodule for early diagnosis on cancer

2012 ◽  
Vol 3 (2) ◽  
pp. 253-255
Author(s):  
Raman Brar
Keyword(s):  
Human Lung ◽  
Research Work ◽  
Vital Role ◽  
Watershed Algorithm ◽  
Segmentation Method ◽  
Resonance Imaging ◽  
Segmentation Methods ◽  
Segmentation Accuracy ◽  
Background Segmentation ◽  
Lung Mri

Image segmentation plays a vital role in several medical imaging programs by assisting the delineation of physiological structures along with other parts. The objective of this research work is to segmentize human lung MRI (Medical resonance Imaging) images for early detection of cancer.Watershed Transform Technique is implemented as the Segmentation method in this work. Some comparative experiments using both directly applied watershed algorithm and after marking foreground and computed background segmentation methods show the improved lung segmentation accuracy in some image cases.

A parallel segmentation method of medical image based on cluster system

2014 ◽  
Author(s):  
Yanjun Peng ◽  
Yuanhong Wang
Keyword(s):  
Medical Image ◽  
Cluster System ◽  
Segmentation Method

Multiresolution Bio-Medical Image Segmentation using Fuzzy C-Means Clustering

2019 ◽  
Vol 8 (4) ◽  
pp. 9548-9551
Keyword(s):  
Image Segmentation ◽  
Medical Image Segmentation ◽  
Experimental Result ◽  
Segmentation Method ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Robust Image ◽  
Multiple Clusters ◽  
Single Pixel ◽  
Popular Image

Fuzzy c-means clustering is a popular image segmentation technique, in which a single pixel belongs to multiple clusters, with varying degree of membership. The main drawback of this method is it sensitive to noise. This method can be improved by incorporating multiresolution stationary wavelet analysis. In this paper we develop a robust image segmentation method using Fuzzy c-means clustering and wavelet transform. The experimental result shows that the proposed method is more accurate than the Fuzzy c-means clustering.

Interactive Ship Infrared Image Segmentation Method Based on Graph Cut and Fuzzy Connectedness

2012 ◽  
Vol 38 (11) ◽  
pp. 1735 ◽  
Author(s):  
Song-Tao LIU ◽  
Hui-Li WANG ◽  
Fu-Liang YIN
Keyword(s):  
Image Segmentation ◽  
Infrared Image ◽  
Graph Cut ◽  
Segmentation Method ◽  
Fuzzy Connectedness ◽  
Infrared Image Segmentation

Multi-model Integrated Weakly Supervised Semantic Segmentation Method

2019 ◽  
Vol 31 (5) ◽  
pp. 800
Author(s):  
Changzhen Xiong ◽  
Hui Zhi
Keyword(s):  
Semantic Segmentation ◽  
Segmentation Method ◽  
Weakly Supervised

A Global Stationary Minimum Level Set Segmentation Method for High-resolution SAR Images

2010 ◽  
Vol 32 (11) ◽  
pp. 2618-2623 ◽  
Author(s):  
Ji-lan Feng ◽  
Zong-jie Cao ◽  
Yi-ming Pi
Keyword(s):  
High Resolution ◽  
Level Set ◽  
Segmentation Method ◽  
Minimum Level ◽  
Sar Images ◽  
Level Set Segmentation
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