Medical image classification using genetic-algorithm based fuzzy-logic approach

2004 ◽  
Vol 13 (4) ◽  
pp. 780 ◽  
Author(s):  
Du-Yih Tsai
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Image Classification ◽  
Medical Image ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Medical Image Classification

scholarly journals A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Dalton Meitei Thounaojam ◽  
Thongam Khelchandra ◽  
Kh. Manglem Singh ◽  
Sudipta Roy
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Fuzzy System ◽  
Boundary Detection ◽  
Shot Boundary Detection ◽  
Detection Approach ◽  
Video Shot ◽  
Shot Boundary ◽  
Fuzzy Logic Approach ◽  
Logic Approach

This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In this, the membership functions of the fuzzy system are calculated using Genetic Algorithm by taking preobserved actual values for shot boundaries. The classification of the types of shot transitions is done by the fuzzy system. Experimental results show that the accuracy of the shot boundary detection increases with the increase in iterations or generations of the GA optimization process. The proposed system is compared to latest techniques and yields better result in terms ofF1scoreparameter.

scholarly journals Distribution Problems, Their Modifications and Applications

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Assignment Problem ◽  
Transportation Problem ◽  
Uncertain Data ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Distribution Problems

In this paper, we deal with well-known distribution problems and discuss their restrictions, extensions and modifications including a possible application in agriculture. We show that the transportation problem can be transformed to an assignment problem using special constraints, but because of NPhardness it needs quite different methods of its solving. Another modification of the transportation problem, the crop problem, has an application in agriculture, but we must deal with uncertain data. We propose a genetic algorithm and fuzzy logic approach for solving these problems.

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