scholarly journals COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS

2020 ◽  
Vol 5 (3) ◽  
pp. 1-9
Author(s):  
Sumit Kaur ◽  
R.K Bansal
Keyword(s):  
Computer Vision ◽  
Comparative Analysis ◽  
Computational Complexity ◽  
Point Of View ◽  
Computational Time ◽  
Time Consumption ◽  
Superpixel Segmentation ◽  
Segmentation Methods ◽  
Computer Vision Applications ◽  
High Computational Complexity

Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and weaknesses. Many methods for the computation of superpixels were already presented. A drawback of most of these methods is their high computational complexity and hence high computational time consumption. K mean based SLIC method shows better performance as compare to other while evaluating on the bases of under segmentation error and boundary recall, etc parameters.

Vision Enhancement in Bad Weather

2018 ◽  
pp. 1802-1819
Author(s):  
Md. Imtiyaz Anwar ◽  
Arun Khosla
Keyword(s):  
Computer Vision ◽  
Comparative Analysis ◽  
Weather Conditions ◽  
Road Accident ◽  
Point Of View ◽  
Turbid Medium ◽  
The World ◽  
Bad Weather

Road accident is a serious issue in most of the countries due to degraded visibility in bad weather such as fog, haze and rain. A better visibility is a key requirement for passenger's safety while maintaining the speed of the vehicle. Researchers throughout the world are focusing to enhance the visibility through bad weather mainly due to fog or haze to minimize accidents. Many efforts are being put up to clearly visualize the scene using computer vision. Classifications of fog and analysis of de-weathering techniques are prime motive of research. This book chapter addresses and summarizes the progress in the development of vision enhancement techniques for road safety in turbid medium, particularly with fog which greatly affects the vision. This chapter also presents a brief comparative analysis on different weather conditions and classification of fog which is important for application point of view.

Vision Enhancement in Bad Weather

2016 ◽  
pp. 65-82
Author(s):  
Md. Imtiyaz Anwar ◽  
Arun Khosla
Keyword(s):  
Computer Vision ◽  
Comparative Analysis ◽  
Weather Conditions ◽  
Road Accident ◽  
Point Of View ◽  
Turbid Medium ◽  
The World ◽  
Bad Weather

Road accident is a serious issue in most of the countries due to degraded visibility in bad weather such as fog, haze and rain. A better visibility is a key requirement for passenger's safety while maintaining the speed of the vehicle. Researchers throughout the world are focusing to enhance the visibility through bad weather mainly due to fog or haze to minimize accidents. Many efforts are being put up to clearly visualize the scene using computer vision. Classifications of fog and analysis of de-weathering techniques are prime motive of research. This book chapter addresses and summarizes the progress in the development of vision enhancement techniques for road safety in turbid medium, particularly with fog which greatly affects the vision. This chapter also presents a brief comparative analysis on different weather conditions and classification of fog which is important for application point of view.

VAT Refund under Conditions of Zero Tax Rate

2007 ◽  
pp. 120-136
Author(s):  
R. Saakyan ◽  
I. Trunin
Keyword(s):  
Comparative Analysis ◽  
Point Of View ◽  
Tax Administration ◽  
Tax Rate ◽  
Export Sector ◽  
Tax Legislation

Main directions of tax legislation development are considered in the article from the point of view of relevancy of zero tax rate implementation and tax refund. Special emphasis is placed on the problem of tax refund delay that undermines the competitiveness of the export sector of economy. Comparative analysis of VAT refund mechanisms in different countries and Russia with respect to effectiveness of tax administration has allowed to formulate some hypotheses concerning relevant parameters of refund and test them with the help of various methods and models.

The role of graining in ensuring food security

2020 ◽  
pp. 75-79
Author(s):  
R. M. Gambarova
Keyword(s):  
Food Security ◽  
Comparative Analysis ◽  
Systems Approach ◽  
Point Of View ◽  
Government Support ◽  
Grain Production ◽  
The Government ◽  
Favorable Conditions ◽  
Grain Farms

Relevance. Grain is the key to strategic products to ensure food security. From this point of view, the creation of large grain farms is a matter for the country's selfsufficiency and it leading to a decrease in financial expense for import. Creation of such farms creates an abundance of productivity from the area and leads to obtaining increased reproductive seeds. The main policy of the government is to minimize dependency from import, create abundance of food and create favorable conditions for export potential.The purpose of the study: the development of grain production in order to ensure food security of the country and strengthen government support for this industry.Methods: comparative analysis, systems approach.Results. As shown in the research, if we pay attention to the activities of private entrepreneurship in the country, we can see result of the implementation of agrarian reforms after which various types of farms have been created in republic.The role of privateentrepreneurshipinthedevelopmentofproduction is great. Тhe article outlines the sowing area, production, productivity, import, export of grain and the level of selfsufficiency in this country from 2015 till 2017.

TRANSLATION OF SOCIAL AND POLITICAL TERMINOLOGY OF CHINESE LANGUAGE AS A PROCESS OF NORMATIVE PRACTICE IN CONTEXT MODELS

2020 ◽  
Vol 6 (3) ◽  
pp. 172-182
Author(s):  
Saodat Nosirova ◽  
Keyword(s):  
Comparative Analysis ◽  
Law Enforcement ◽  
Chinese Language ◽  
Integrated Approach ◽  
Point Of View ◽  
Modern Chinese ◽  
Normative Practice ◽  
Context Models

The article is devoted to a comparative analysis of the socio -political terminology of the modern Chinese language.The purpose of the article is to search for an integrated approach to the study of the cognitive side of social and political terms of the Chinese language from the point of view of law enforcement in the process of translating official materials from Chinese into Uzbek and / or Russian and vice versa

scholarly journals Computational Complexity Reduction of Neural Networks of Brain Tumor Image Segmentation by Introducing Fermi–Dirac Correction Functions

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 223
Author(s):  
Yen-Ling Tai ◽  
Shin-Jhe Huang ◽  
Chien-Chang Chen ◽  
Henry Horng-Shing Lu
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Computational Complexity ◽  
High Performance ◽  
Low Cost ◽  
Structural Complexity ◽  
Correction Function ◽  
Computational Time ◽  
Learning Methods ◽  
Band Theory

Nowadays, deep learning methods with high structural complexity and flexibility inevitably lean on the computational capability of the hardware. A platform with high-performance GPUs and large amounts of memory could support neural networks having large numbers of layers and kernels. However, naively pursuing high-cost hardware would probably drag the technical development of deep learning methods. In the article, we thus establish a new preprocessing method to reduce the computational complexity of the neural networks. Inspired by the band theory of solids in physics, we map the image space into a noninteraction physical system isomorphically and then treat image voxels as particle-like clusters. Then, we reconstruct the Fermi–Dirac distribution to be a correction function for the normalization of the voxel intensity and as a filter of insignificant cluster components. The filtered clusters at the circumstance can delineate the morphological heterogeneity of the image voxels. We used the BraTS 2019 datasets and the dimensional fusion U-net for the algorithmic validation, and the proposed Fermi–Dirac correction function exhibited comparable performance to other employed preprocessing methods. By comparing to the conventional z-score normalization function and the Gamma correction function, the proposed algorithm can save at least 38% of computational time cost under a low-cost hardware architecture. Even though the correction function of global histogram equalization has the lowest computational time among the employed correction functions, the proposed Fermi–Dirac correction function exhibits better capabilities of image augmentation and segmentation.

scholarly journals A NOVEL IMAGE SEGMENTATION APPROACH BASED ON NEUTROSOPHIC SET AND IMPROVED FUZZY C-MEANS ALGORITHM

2011 ◽  
Vol 07 (01) ◽  
pp. 155-171 ◽  
Author(s):  
H. D. CHENG ◽  
YANHUI GUO ◽  
YINGTAO ZHANG
Keyword(s):  
Image Segmentation ◽  
Point Of View ◽  
Neutrosophic Set ◽  
Convergence Criterion ◽  
Complex Objects ◽  
Fuzzy C Means ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Segmentation Approach ◽  
Fuzzy C Means Algorithm

Image segmentation is an important component in image processing, pattern recognition and computer vision. Many segmentation algorithms have been proposed. However, segmentation methods for both noisy and noise-free images have not been studied in much detail. Neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interaction with different ideational spectra. However, neutrosophic set needs to be specified and clarified from a technical point of view for a given application or field to demonstrate its usefulness. In this paper, we apply neutrosophic set and define some operations. Neutrosphic set is integrated with an improved fuzzy c-means method and employed for image segmentation. A new operation, α-mean operation, is proposed to reduce the set indeterminacy. An improved fuzzy c-means (IFCM) is proposed based on neutrosophic set. The computation of membership and the convergence criterion of clustering are redefined accordingly. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can segment images accurately and effectively. Especially, it can segment the clean images and the images having different gray levels and complex objects, which is the most difficult task for image segmentation.

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