Téléchargez le livre : Machine Learning in Aquaculture

Machine Learning in Aquaculture

Hunger Classification of Lates calcarifer de

Éditeur :

Springer


Collection :

SpringerBriefs in Applied Sciences and Technology

Paru le : 2020-01-02

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Description

This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish growth is essential, since they have implications for higher productivity in fish farms. Computer vision and machine learning techniques make it possible to quantify the subjective perception of hunger behaviour and so allow food to be provided as necessary. The book analyses the conceptual framework of motion tracking, feeding schedule and prediction classifiers in order to classify the hunger state, and proposes a system comprising an automated feeder system, image-processing module, as well as machine learning classifiers. Furthermore, the system substitutes conventional, complex modelling techniques with a robust, artificial intelligence approach. The findings presented are of interest to researchers, fish farmers, and aquaculture technologist wanting to gain insights into the productivity of fish and fish behaviour.
Pages
60 pages
Collection
SpringerBriefs in Applied Sciences and Technology
Parution
2020-01-02
Marque
Springer
EAN papier
9789811522369
EAN PDF
9789811522376
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
6
Taille du fichier
3092 Ko
Prix
52,74 €
EAN EPUB
9789811522376
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
6
Taille du fichier
8284 Ko
Prix
52,74 €

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