Mohd Razman, Mohd Azraai and Abdul Majeed, Anwar P.P. and Musa, Rabiu Muazu and Taha, Zahari and Susto, Gian-Antonio and Mukai, Yukinori (2020) Monitoring and feeding integration of demand feeder systems. In: Machine learning in aquaculture: hunger classification of Lates calcarifer. SpringerBriefs in Applied Sciences and Technology . Springer, Singapore, pp. 11-24. ISBN 978-981-15-2236-9
PDF (CHAPTER 2)
- Published Version
Restricted to Registered users only Download (1MB) | Request a copy |
||
|
PDF (SCOPUS)
- Supplemental Material
Download (344kB) | Preview |
Abstract
This chapter highlights the findings of the developmental monitoring systems for swimming pattern or motion analysis with regard to feeding behaviour. A benchmark for examining the framework on how scientists control fish in animal variable function factors was gathered and referred to gauge the adequate design in constructing a viable device. The validation of image processing and automated demand feeder to determine the results will also be considered, as a validation aspect between the system of tracking and the behaviour of the Lates calcarifer where the pixel intensity will be extracted as the features. The results of this chapter will enable the reader on the development of an integrated feeder scheme that consolidates surveillance scheme to identify the feeding behaviour and relation towards the specific growth rate (SGR).
Item Type: | Book Chapter |
---|---|
Additional Information: | 6616/82243 |
Uncontrolled Keywords: | Automated demand feeder, Image processing, Lates calcarifer, Pixel intensity, Specific growth rate |
Subjects: | Q Science > Q Science (General) S Agriculture > SH Aquaculture. Fisheries. Angling S Agriculture > SH Aquaculture. Fisheries. Angling > SH151 Aquaculture - Fish Culture |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Science Kulliyyah of Science > Department of Marine Science |
Depositing User: | Dr. Yukinori Mukai |
Date Deposited: | 16 Oct 2020 15:58 |
Last Modified: | 16 Oct 2020 15:58 |
URI: | http://irep.iium.edu.my/id/eprint/82243 |
Actions (login required)
View Item |