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Machine Learning in Aquaculture: Hunger Classification of Lates Calcarifer (2020)

Machine Learning in Aquaculture: Hunger Classification of Lates Calcarifer (2020)

No customer reviews yet ISBN 9789811522369 Springer

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.

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BrandSpringer
Pub dateJan 4, 2020
ISBN-109811522367
ISBN-139789811522369
LanguageEnglish
Dimensions9.21 × 0.14 × 6.14 in
Weight0 lb
Last updated 2026-03-20 05:50
$57.47
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