Chapter: Locust Search Algorithm Applied to Multi-threshold Segmentation

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Home > New Advancements in Swarm Algorithms: Operators and Applications > Locust Search Algorithm Applied to Multi-threshold Segmentation

New Advancements in Swarm Algorithms: Operators and Applications |

Erik Cuevas; Fernando Fausto; Adrián González

Springer International Publishing

New Advancements in Swarm Algorithms: Operators and Applications

Locust Search Algorithm Applied to Multi-threshold Segmentation

Chapter Info

Authors

Erik Cuevas; Fernando Fausto; Adrián González

ARI Id

1665177299041_5172989

Access

Not Available Free

Pages

211-240

DOI

10.1007/978-3-030-16339-6_8

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-030-16339-6_8

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Chapters/Headings	Author(s)	Pages	Info
Front Matter		i-xv
An Introduction to Nature-Inspired Metaheuristics and Swarm Methods	Erik Cuevas; Fernando Fausto; Adrián González	1-41
Metaheuristics and Swarm Methods: A Discussion on Their Performance and Applications	Erik Cuevas; Fernando Fausto; Adrián González	43-67
The Selfish Herd Optimizer	Erik Cuevas; Fernando Fausto; Adrián González	69-109
The Swarm Method of the Social-Spider	Erik Cuevas; Fernando Fausto; Adrián González	111-137
The Locust Swarm Optimization Algorithm	Erik Cuevas; Fernando Fausto; Adrián González	139-159
A Swarm Algorithm Inspired by the Collective Animal Behavior	Erik Cuevas; Fernando Fausto; Adrián González	161-188
Auto-calibration of Fractional Fuzzy Controllers by Using the Swarm Social-Spider Method	Erik Cuevas; Fernando Fausto; Adrián González	189-209
Locust Search Algorithm Applied to Multi-threshold Segmentation	Erik Cuevas; Fernando Fausto; Adrián González	211-240
Multimodal Swarm Algorithm Based on the Collective Animal Behavior (CAB) for Circle Detection	Erik Cuevas; Fernando Fausto; Adrián González	241-278
Locust Search Algorithm Applied for Template Matching	Erik Cuevas; Fernando Fausto; Adrián González	279-296
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