Work

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

Year: 2024

Type: article

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.

Source: J-KOMA Jurnal Ilmu Komputer dan Aplikasi

DOI: 10.21009/j-koma.v7i1.04

Authors: Hafizhun Alim, Eka Suryana Muhammad, Mulyono

Institution: State University of Jakarta

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Life below water

Open Access status: diamond

OpenAlex ID: W4414301071

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