39,99 €
versandkostenfrei*
inkl. MwSt.
Versandfertig in 6-10 Tagen
20 °P sammeln
  • Broschiertes Buch

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…mehr

Produktbeschreibung
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.
Autorenporträt
Mr. Mohd Azraai Mohd Razman graduated his first degree from the University of Sheffield, United Kingdom, in Mechatronics Engineering in 2010. He then obtained his M.Eng. by 2014 from Universiti Malaysia Pahang (UMP) in Mechatronics Engineering and currently pursuing his Ph.D. at UMP as well. He did his visiting Ph.D. at University of Padova, Italy, in 2018 where he focuses on computer vision and machine learning. His research interests include optimization techniques, control systems, signal processing, instrumentation in aquaculture, sports engineering, as well as machine learning.
Dr. Anwar P.P. Abdul Majeed graduated with a first-class honours B.Eng. in Mechanical Engineering from Universiti Teknologi MARA (UiTM), Malaysia. He obtained an M.Sc. in Nuclear Engineering from Imperial College London, United Kingdom. He then received his Ph.D. in Rehabilitation Robotics under the supervision of Prof. Dr. Zahari Taha from Universiti Malaysia Pahang (UMP). He is currently serving as a senior lecturer at the Faculty of Manufacturing and Mechatronics Engineering Technology, UMP. He is an active research member at the Innovative Manufacturing, Mechatronics and Sports Laboratory, UMP. His research interests include rehabilitation robotics, computational mechanics, applied mechanics, sports engineering, renewable and nuclear energy, sports performance analysis, as well as machine learning.