Fish Movement Tracking Menggunakan Metode Gaussian Mixture Models (GMM) dan Kalman Filter

Alim, Hafizhun and Muhammad, Eka Suryana and Mulyono, Mulyono (2024) Fish Movement Tracking Menggunakan Metode Gaussian Mixture Models (GMM) dan Kalman Filter. J-KOMA Jurnal Ilmu Komputer dan Aplikasi, 1 (1). ISSN 2620-4827

Full text not available from this repository.
Official URL: https://journal.unj.ac.id/unj/index.php/jkoma/arti...

Abstract

Indonesia Fish industries is one of the large in the world for market capital which covers for both natural growing and intensive culture. One part of the most challenging problem for intensive culture is related to counting when harvesting which been done by hand all this time. In order to be more efficient, we propose this task can be done through automation with Gussian Mixture Model. The proposed system proven been able with low error rate that also resulting close estimate of fish object counting giiven various background videos.

Item Type: Article
Subjects: Sains > Matematika > Ilmu Komputer
Depositing User: OJS LPPM UNJ .
Date Deposited: 09 Mar 2025 04:03
Last Modified: 09 Mar 2025 04:03
URI: http://repository.unj.ac.id/id/eprint/55303

Actions (login required)

View Item View Item