Nur Amirah Shafiqah, Salleh (2022) Fish Segmentation And Classification For Large Scale Dataset From Turkey. College of Engineering, Universiti Malaysia Pahang Al-Sultan Abdullah.
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EA18024_Nur Amirah Shafiqah Salleh_Thesis - NUR AMIRAH SHAFIQAH SALLEH.pdf - Accepted Version Download (4MB) | Preview |
Abstract
Classification helps humans learn about different kinds of fish, their features, similarities, and differences. In this project, images from eight fish types are collected from a supermarket’s fish counter; every kind of fish has 1000 images. This study aims to extract fish’s texture, color, and shape and utilize K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) classifiers to categorize the eight different types of fish in Izmir, Turkey. The results from the experiment show the accuracy of KNN is 100% and SVM is 100%.
| Item Type: | Undergraduates Project Papers |
|---|---|
| Additional Information: | SV: Dr. Mahfuzah Binti Mustafa |
| Uncontrolled Keywords: | fish, K-Nearest Neighbors (KNN), Support Vector Machine (SVM) classifiers |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | College of Engineering |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 05 Jan 2024 08:23 |
| Last Modified: | 05 Jan 2024 08:23 |
| URI: | http://umpir.ump.edu.my/id/eprint/39878 |
| Download Statistic: | View Download Statistics |
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