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Book Cover
E-book
Author Mohd Razman, Mohd Azraai

Title Machine learning in aquaculture : hunger classification of Lates Calcarifer / Mohd Azraai Mohd Razman, Anwar P.P. Abdul Majeed, Rabiu Muazu Musa, Zahari Taha, Gian-Antonio Susto, Yukinori Mukai
Published Singapore : Springer, 2020

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Description 1 online resource (64 pages)
Series SpringerBriefs in Applied Sciences and Technology Ser
SpringerBriefs in applied sciences and technology.
Contents 1 Introduction -- 2 Monitoring and feeding integration of demand feeder systems -- 3 Image processing features extraction on fish behaviour -- 4 Time-series identification of fish feeding behaviour
Summary 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
Bibliography Includes bibliographical references
Notes Print version record
Subject Fishes -- Feeding and feeds -- Data processing
Machine learning.
Machine Learning
Machine learning
Form Electronic book
Author Majeed, Anwar P. P. Abdul.
Muazu Musa, Rabiu
Zahari Taha.
Susto, Gian Antonio
Mukai, Yukinori
ISBN 9789811522376
9811522375
9811522367
9789811522369
9789811522383
9811522383