Shahriman, Ahmad Syahmi
(2021)
Fish classification using machine learning / Ahmad Syahmi Shahriman.
Degree thesis, Universiti Teknologi MARA, Perak.
Abstract
Fish classification may be identified manually from its characteristics such as the scale of the fish, shape of the head of a fish, the size of tail, the size of the body and more, which can be confusing to non-professional people. The purpose of this project is to assist people that are non-expert, to identify the type of fish based on the image given to the project. The project will consist of a fish dataset of commonly sold fish in Malaysia. The user is able to use the application which is available for the Android operating system, and able to detect the type of fish the user has given to the application. The other purpose of the project is to educate people about fish, as most people in Malaysia lack of knowledge about fisheries.
Metadata
Item Type: | Thesis (Degree) |
---|---|
Creators: | Creators Email / ID Num. Shahriman, Ahmad Syahmi 2020994875 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Isawasan, Pradeep UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Mobile computing Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Operating systems (Computers) > Android Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science) |
Divisions: | Universiti Teknologi MARA, Perak > Tapah Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Computer Science |
Keywords: | Fish classification; machine learning |
Date: | July 2021 |
URI: | https://ir.uitm.edu.my/id/eprint/59446 |
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