Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review

被引:45
作者
Chakraborty, Sanjoy [1 ,2 ]
Saha, Apu Kumar [3 ]
Ezugwu, Absalom E. [4 ]
Agushaka, Jeffrey O. [4 ,5 ]
Abu Zitar, Raed [6 ]
Abualigah, Laith [7 ,8 ,9 ]
机构
[1] Iswar Chandra Vidyasagar Coll, Dept Comp Sci & Engn, Belonia, Tripura, India
[2] Natl Inst Technol Agartala, Dept Comp Sci & Engn, Agartala, Tripura, India
[3] Natl Inst Technol Agartala, Dept Math, Agartala 799046, Tripura, India
[4] Univ KwaZulu Natal, Sch Math Stat & Comp Sci, King Edward Rd, ZA-3201 Pietermaritzburg, Kwazulu Natal, South Africa
[5] Fed Univ Lafia, Dept Comp Sci, Lafia 950101, Nigeria
[6] Sorbonne Univ Abu Dhabi, Sorbonne Ctr Artificial Intelligence, Abu Dhabi 38044, U Arab Emirates
[7] Al Ahliyya Amman Univ, Hourani Ctr Appl Sci Res, Amman, Jordan
[8] Middle East Univ, Fac Informat Technol, Amman 11831, Jordan
[9] Univ Sains Malaysia, Sch Comp Sci, George Town 11800, Malaysia
关键词
ARTIFICIAL BEE COLONY; EIGENVECTOR-BASED CROSSOVER; FEATURE-SELECTION; GLOBAL OPTIMIZATION; CONTROL PARAMETERS; MUTATION OPERATOR; ALGORITHM; SEGMENTATION; SEARCH; ENSEMBLE;
D O I
10.1007/s11831-022-09825-5
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. DE has grown steadily since its beginnings due to its ability to solve various issues in academics and industry. Different mutation techniques and parameter choices influence DE's exploration and exploitation capabilities, motivating academics to continue working on DE. This survey aims to depict DE's recent developments concerning parameter adaptations, parameter settings and mutation strategies, hybridizations, and multi-objective variants in the last twelve years. It also summarizes the problems solved in image processing by DE and its variants.
引用
收藏
页码:985 / 1040
页数:56
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